Abstract
Zinc (Zn2+) is an essential metal in biology and its bioavailability is highly regulated. Many cell types exhibit fluctuations in Zn2+ that appear to play an important role in cellular function. However, the detailed molecular mechanisms by which Zn2+ dynamics influence cell physiology remain enigmatic. Here, we use a combination of fluorescent biosensors and cell perturbations to define how changes in intracellular Zn2+ impact kinase signaling pathways. By simultaneously monitoring Zn2+ dynamics and kinase activity in individual cells, we quantify changes in labile Zn2+ and directly correlate changes in Zn2+ with ERK and Akt activity. Under our experimental conditions, Zn2+ fluctuations are not toxic and do not activate stress-dependent kinase signaling. We demonstrate that while Zn2+ can non-specifically inhibit phosphatases leading to sustained kinase activation, ERK and Akt are predominantly activated via upstream signaling, and through a common node via Ras. We provide a framework for quantification of Zn2+ fluctuations and correlate these fluctuations with signaling events in single cells to shed light on the role that Zn2+ dynamics play in healthy cell signaling.
Significance Statement While zinc (Zn2+) is a vital ion for cell function and human health, little is known about the role it plays in regulating cell signaling. Here, we use fluorescent tools to study the interaction between Zn2+ and cell signaling pathways that play a role in cell growth and proliferation. Importantly, we use small, non-toxic Zn2+concentrations to ensure that our Zn2+ changes are closer to what cells would experience in the body and not stress-inducing. We also demonstrate that these signaling changes are driven by Ras activation, which contradicts one of the major hypotheses in the field. Our sensors shed light on how cells respond to a very important micronutrient in real time.
Introduction
Zinc (Zn2+) is an essential metal in biology, with approximately ten percent of the proteins encoded by the human genome predicted to bind Zn2+,1. All cells maintain and regulate a small pool of labile Zn2+ that can be exchanged among Zn2+ binding proteins and Zn2+ biosensors. The concentration of labile Zn2+ in the cytosol, measured in the hundreds of picomolar range2–5, falls within the affinity range of many Zn2+ binding proteins, suggesting that under normal conditions many of these proteins will bind Zn2+ and function properly. However, some Zn2+ binders may need higher Zn2+ concentrations in order to function6. Furthermore, there is growing evidence that mammalian cells experience fluctuations in available Zn2+, and these dynamics have been shown to be important for cell physiology7–11.
In addition to serving as an important biological cofactor12, there are increasing examples that Zn2+ also plays a role in biological signaling. Crosstalk has been observed between Zn2+ dynamics and calcium signaling where increases in cytosolic Zn2+ lead to decrease in ER calcium, and conversely increases in cytosolic calcium change Zn2+ homeostasis in the ER3. Zn2+ sequestration has been shown to block cell cycle progression in both meiotic oocytes13 and mitotic cells14–16. At a molecular level, picomolar concentrations of Zn2+ potentiate the response of the ryanodine receptor in cardiomyocytes17. Zn2+ has also been implicated in metabotropic signaling via the G-protein-coupled receptor 39 (GPR3918, direct modulation of Protein Kinase C activity19, and activation of MAPK kinase signaling pathways in neurons20, cardiomyocytes21, and mast cells7. While the above studies demonstrate that Zn2+ fluctuations influence cellular processes, in many cases the molecular details of how Zn2+ interacts with canonical signaling pathways, second messengers, or serves as a signal itself are unclear. This is especially true for the MAPK pathway.
MAPK signaling plays a role in cell proliferation, differentiation, and development, and is one of the most well-studied signaling pathways22. A connection between MAPK signaling and Zn2+ was first reported in 1996 when it was observed that addition of 300 μM ZnCl2 to 3T3 fibroblasts led to increased phosphorylation of ERK1/2 kinases in the MAPK pathway23. Early studies used epithelial cell lines to study the connection between Zn2+ and ERK signaling23,24. More recently, Zn2+ elevation has been demonstrated to increase ERK phosphorylation in dissociated neurons and transformed HT22 cells, where ERK signaling has been linked to synaptic plasticity and memory consolidation25,26,20. The mechanism of ERK activation by Zn remains enigmatic. The leading hypothesis has been that Zn2+ inhibits protein phosphatases, leading to sustained ERK activation. This idea is supported by the observation that ERK-directed phosphatase PP2A activity is reduced when Zn2+ is added to cell lysates20,25. Furthermore, it has been demonstrated that certain phosphatases are inhibited by nano- and picomolar concentrations of Zn2+ in vitro, although these phosphatases are not known to directly interact with ERK1/227,28. However, it is unclear how these bulk in vitro analyses relate to the role of Zn2+ fluctuations in living cells.
In this work we set out to dissect the connection between Zn2+ and ERK in an effort to elucidate the mechanism of activation. Using a combination of kinase translocation reporters and a FRET-sensor for Zn2+ we quantified the changes in intracellular Zn2+ in response to subtle extracellular perturbations and correlated them directly with changes in kinase activity at the single cell level. We found that while elevated Zn2+ broadly inhibits phosphatase activity to some extent in vitro, in live cells Zn2+ primarily activates ERK via upstream signaling, suggesting that ERK phosphatase inhibition can’t fully account for Zn2+-induced increase in ERK activity. Finally, we demonstrate that our Zn2+ conditions activate Ras and Akt signaling along with ERK, but that few other kinases are activated, including stress-response kinases JNK, p38, and p53. We therefore propose a mechanism of action where Zn2+ activates ERK and Akt pathways upstream of Ras, while the specific Zn2+-protein interaction remains elusive.
Results
Quantification of Zn2+ manipulations
One limitation of previous studies was the treatment of cells with high concentrations of Zn2+ and the lack of quantification of how these extracellular perturbations altered the intracellular Zn2+ concentration. Therefore, we used genetically-encoded Förster resonance energy transfer (FRET)-based Zn2+ sensors to quantify the changes in intracellular Zn2+ in response to a series of applied extracellular Zn2+ solutions. The FRET ratios of these sensors are proportional to the concentration of labile Zn2+ so that a higher ratio corresponds to higher Zn2+. Addition of ZnCl2 extracellularly to HeLa cells, without the use of ionophores, causes a rapid and dose-dependent increase in intracellular Zn2+ that saturates in approximately 40 min (Fig 1). After measuring the resting FRET ratio, cells were subjected to perturbations that deplete or saturate the sensor (min and max FRET ratio, respectively). As described in Methods, parameters obtained from this in situ calibration can be used to approximate the concentration of labile Zn2+ under resting conditions and after Zn2+ addition. We used two cytosolic sensors with different apparent dissociation constants for Zn2+ (NES-ZapCV2, Kd = 5.3 ⋂M; NES-ZapCV5, Kd = 300 nM)29. Resting Zn2+ in the cytosol was in the low pM range, consistent with previous measurements2,4,5. Addition of 10 to 40 μM Zn2+ caused intracellular Zn2+ to increase to the low micromolar range (Fig 1). The higher affinity ZapCV2 sensor became fully saturated upon addition of 40 μM Zn2+ (Fig 1a), so to quantify the range of Zn2+ concentrations in cells the lower affinity ZapCV5 sensor was also used to measure Zn2+ influx (Fig 1b). ZapCV5 has a low dynamic range (~1.4 vs ~2 for ZapCV2), which can lead to overestimation of Zn2+ concentrations due to the inverse relationship between dynamic range and fractional saturation of the sensor regardless of apparent KD30. The ZapCV5 data have therefore been reported as “less than” the calculated value. Calculations were made using the asymptote of the curve fit equations for each condition (Fig 1c, ZapCV5 data not shown) to provide a reliable Zn2+ estimate but minimize the overall time cells are exposed to treatment and light. These results demonstrate that increasing the concentration of extracellular Zn2+ leads to a titratable increase in intracellular Zn2+ levels. To put these perturbations in perspective, the concentration of Zn2+ in human serum is approximately 15 μM31 and cell culture medias vary from 1-40 μM32, with most of the Zn2+ being supplied by the serum.
We want to clearly distinguish between our goal of understanding the impacts of small Zn2+ changes on cell signaling processes in healthy cells compared to the study of Zn2+ toxicity following traumatic brain injuries, epilepsy, and stroke26,33,34. Therefore, we measured whether Zn2+ perturbations induce cell toxicity using a CelITiter Gio assay. As demonstrated in Fig 1d, Zn2+ manipulations up to 100 μM do not cause significant levels of cell death in HeLa cells. Interestingly, we did find that the Zn2+ chelator tris(2-pyridylmethyl)amine (TPA) can be toxic to cells at concentrations as low as 1 μM, suggesting that HeLa cells are better able to withstand Zn2+ increases than decreases.
Zn2+ activates select kinases including ERK and Akt
We next sought to measure kinase activation by Zn2+ in single cells and populations of cells to examine dynamics, heterogeneity, and breadth of kinase activation. Using a combination of genetically encoded reporters, cytosolic Zn2+ and ERK activity can be simultaneously monitored in live cells in response to cellular perturbations. The ZapCV2 sensor was used to monitor changes in the labile Zn2+ pool and an ERK kinase translocation reporter (KTR)35 was used to monitor ERK activity in live cells. Simultaneous imaging of Zn2+ and ERK activity reveals that upon treatment with 40 μM Zn2+, cytosolic Z⋂2+ rises immediately and precedes the increase in ERK activity (Fig. 2a). There is variability from cell to cell in both the magnitude of Zn2+ increase and ERK activation, but all cells with increased ERK activity exhibited an increase in Zn2+ (Fig. 2b,c). These results suggest that low micromolar Zn2+ influx into cells leads to a rapid increase in ERK activity in live cells.
To better understand the breadth of the cell signaling response to Zn2+, we then performed a kinase phospho array on cells where 40 μM Zn2+ was added for 30 minutes. We found that low micromolar increases in Zn2+ lead to robust phosphorylation of a few cell signaling proteins, including ERK1/2, the transcription factor CREB that acts downstream of ERK, and GSK-3α/ß, which is phosphorylated and inactivated by Akt. Notably, proteins that participate in cell stress pathways, including JNK, p38, Chk-2, and p53, are not activated by Zn2+ under these conditions. JNK was confirmed to be insensitive to Zn2+ via live-cell imaging with a JNK translocation sensor (Supp Fig S1). Furthermore, MAPK pathway stimulating proteins PYK2, Src, and EGFR also do not appear to be activated by Zn2+ (Figure 3a, Supp Table S2). When analyzed by western blot, cell populations treated with different concentrations of Zn2+ demonstrate robust phosphorylation of proteins both upstream (MEK) and downstream (CREB) of ERK (Figure 3b). Combined, the phospho array and western blot results suggest that Zn2+ elevation activates a number of kinases in the MAPK pathway, both upstream and downstream of ERK. However, Zn2+ does not induce widespread non-specific increase in kinase activity, arguing against broad spectrum inhibition of phosphatases by Zn2+ under these conditions. Finally, the Zn2+ treatments used here do not activate stress response-related kinases.
To test whether Zn2+ was activating calcium signaling pathways, that in turn led to ERK activation, we expressed the ERK translocation sensor in conjunction with the D3cpV FRETbased calcium biosensor36. Zn2+, but not treatments that elevate calcium (Ca2+/ionomycin and histamine), activated ERK. Conversely, Zn2+ did not lead to changes in cytosolic calcium levels (Supp Fig S2). These experiments demonstrate that elevation of cytosolic Zn2+ does not lead to detectable changes in cytosolic Ca2+ and hence Zn2+-induced ERK activation does not occur by indirect activation of Ca2+ signaling.
Zn2+ leads to activation of both ERK and Akt, as demonstrated by cells expressing the Akt translocation sensor FoxO1-Clover37, ERK-KTR-mCherry, and the nuclear marker H2B-Halo imaged using JF646-Halo dye. Both Akt and ERK are stimulated by Zn2+ in a titratable manner, and sensor signal appears to saturate between 20 and 40 μM Zn2+ (Figure 4a,b). While the activation of kinases by Zn2+ varies from cell to cell, the pattern of activation of ERK and Akt is similar, suggesting a common activation mechanism or pathway crosstalk (Figure 4c). Data are sorted by initial Akt activity to demonstrate that activation by Zn2+ is independent of initial kinase activity.
While experiments in this paper were conducted in HeLa cells for ease of use, similar patterns of ERK activation by 40 μM Zn2+ were seen in non-cancer mammary epithelial MCF10A cells and the mouse hippocampal neuronal cell line HT-22 (Supp Fig S3). These results demonstrate that activation of ERK by Zn2+ is a general phenomenon in multiple mammalian cell types.
Mechanistic insight into ERK activation byZn2+
Previous research has suggested that the increase in ERK activity upon Zn2+ treatment may result from Zn2+ inhibition of phosphatases20,25. However, many of these studies were performed on cell lysates or in vitro. To explore whether this mechanism could explain ERK activation in our system, we carried out an ERK phosphatase assay on cells treated with Zn2+ under conditions analogous to our imaging experiments, followed by lysis. As a positive control, we also measured phosphatase activity in lysed cells. Briefly, His-tagged dualphosphorylated ERK was incubated with whole cell lysate from cells treated with TPA or Zn2+ for 30 minutes. Alternately, His-ppERK was incubated with lysate from untreated cells to which we added Zn2+, TPA, phosphatase inhibitor (BCI-hydrochloride), or λPPase after lysis (Fig 5a). His-ERK was then removed by nickel beads and the extent of de-phosphorylation was determined via western blot for total and phosphorylated ERK. Zn2+ added to cells pre and post-lysis resulted in a decrease of ERK de-phosphorylation, suggesting that Zn2+ can inhibit ERK-directed phosphatases. Our results are in line with previous research25, namely that treatment of cell lysates with Zn2+ reduces phosphatase activity. Further, we now show that the low μM increases in cytosolic Zn2+ upon treatment of intact cells, also reduce phosphatase activity. However, while this assay demonstrates that phosphatase inhibition can contribute to increased ERK phosphorylation, it does not implicate ERK phosphatases directly. This is especially the case given that we observe robust activation of upstream kinases (e.g. MEK) and similar activation patterns for ERK and Akt, suggesting a common upstream activator.
To determine whether Zn2+ can inhibit ERK-directed phosphatases, we performed an in-vitro inhibition assay with the ERK-selective dual-specificity phosphatase DUSP6 (MKP-3)38. Three separate experiments with Zn2+ concentrations from 76 pM to 2.5 mM (Supp Table S3) were overlaid and converged on an IC50 of 51.3 μM, which demonstrates that DUSP6 activity is inhibited by Zn2+, but at concentrations well above cellular Zn2+ levels (Figure 5b). Together the data suggest that while phosphatase inhibition by Zn2+ may play a role in ERK activation, the concentration of Zn2+ required for inhibition of an ERK-directed phosphatase is higher than the intracellular concentration in our studies. Therefore, it seems unlikely that direct inhibition of ERK phosphatases is the dominant mechanism in cells.
While phosphatases can be inhibited by Zn2+ in vitro, the work with DUSP6 suggests that ERK-directed phosphatases may be inhibited at supraphysiological concentrations, and therefore phosphatase inhibition may only play a small role in ERK activation by Zn2+ in cells. Further, bulks assays (western blot and phospho-array) suggested activation of the MAPK pathway upstream of ERK. To further characterize the extent of activation at the single cell level, we used a variety of kinase inhibitors and the ERK translocation sensor in imaging experiments. MEK was shown to be activated by Zn2+ in Fig 3b, so first we sought to explore the effect of MEK inhibition on ERK activation by Zn2+. We show that MEK inhibition by CI-1040 prior to Zn2+ treatment greatly decreases the extent of ERK activation by Zn2+ (Fig 6a). ERK activation is not totally abolished, suggesting that either inhibition was not complete or that downstream phosphatase inhibition also plays a small role in increasing ERK activity. Inhibition of the upstream growth factor receptor EGFR with Gefitinib, however, had no effect of Zn2+-induced ERK activation (Fig. 6a). Furthermore, when cells are stimulated with Zn2+, followed by inhibitors, MEK inhibition leads to a decrease in Zn2+-activated ERK signaling, whereas EGFR inhibition does not (Figure 6b), indicating that a significant portion of Zn2+ activation of the pathway occurs upstream of MEK but downstream of activation of the receptor tyrosine kinase EGFR. In an extended time-course, cells activated by both Zn2+ and EGF experience similar rates of ERK signal decay upon addition of a MEK inhibitor, suggesting a similar upstream signaling process for both Zn2+ and growth factors (Fig 6c).
Finally, to explore potential activation mechanisms upstream of both ERK and Akt, we used the RaichuEV-Ras FRET sensor39 to determine whether Zn2+ activates the Ras GTP-ase. We demonstrated that Zn2+ activates Ras to an extent similar to EGF activation (Figure 6d). The Ras FRET sensor exhibits a low dynamic range, making it difficult to infer further about magnitude or dynamics of Ras activation. We can conclude, however, that Zn2+ is capable of activating Ras, which is upstream of both ERK and Akt. These results implicate Ras in the Zn2+-dependent activation of both cell signaling pathways.
Discussion
The traditional model of zinc in biology is that Zn2+ functions as a cofactor for a number of proteins, either to maintain their structure or facilitate catalysis, and these proteins are thought to constitutively bind Zn2+ 12,1,40. Recently, we have seen an increase in examples of Zn2+ dynamics in cells7,8,3,41,11 and evidence that Zn2+ can play a regulatory role for a variety of cell processes7,42–44. Although Zn2+ has long been suggested to serve as a cellular signal, much like calcium, the precise molecular details of how Zn2+ accomplishes this task remains elusive for most systems.
One of the challenges in defining how changes in Zn2+ influence cellular processes is that, like many trace essential elements, too little or too much Zn2+ can activate stress pathways and induce toxicity45–47. It has been difficult to define what constitutes physiological zinc fluctuations. A widely used approach to elevate cellular zinc is to use the ionophore pyrithione to shuttle zinc into cells. However, pyrithione is not an innocent ligand. Pyrithione inhibits the growth of yeast and can act as a copper ionophore, perturbing both copper and iron homeostasis48. Pyrithione with Zn2+ can increase susceptibility of cells to oxidative stress49 and inhibit the growth of human skin cells, including DNA synthesis50, and has been implicated in several cell death pathways including canonical apoptosis51, p53-independent apoptosis via ERK activation52, and non-apoptotic cell death via ATP depletion and bio-energetic collapse53. Furthermore, the field has suffered from lack of quantification of how cellular perturbations of Zn2+ alter intracellular Zn2+ levels. Recent work has shown that subtle, more physiological, changes in zinc can influence oocyte maturation10, epigenetic chromatin covalent modifications54, gene expression in neurons55, and the mammalian proliferation-quiescence decision16.
The connection between Zn2+ and kinase signaling has been studied in a variety of systems. Both Zn2+ excess25,26 and depravation56,57 have been linked to ERK-dependent cell death in neurons and neuronal cell lines. In myogenic cells (skeletal muscle precursor), Zn2+ addition was shown to promote proliferation and prevent differentiation through both ERK and Akt signaling58. High concentrations of Zn2+ or zinc pyrithione have also been shown to activate other kinase signaling pathways in cells including JNK and p38 stress-related kinases59,60, Src family kinases61–63, protein kinase C19, and the zinc-sensing receptor GPR3964,18. Finally, we demonstrate that three different cell lines exhibit Zn2+-dependent ERK activation, suggesting this may be a widespread phenomenon in a variety of cell types.
In this study we used a model cell line to quantify Zn2+ fluctuations in the cytosol of cells in the absence of ionophores or chelators. Our Zn2+ conditions elevate Zn2+ into the low micromolar range. This zinc influx is several orders of magnitude larger than the low nanomolar Zn2+ transient seen upon stimulation of dissociated neurons11, suggesting that our results likely amplify the cell signaling response to physiological Zn2+ fluxes. However, using 40 μM Zn2+, we were able to detect changes in multiple kinase signaling pathways while preventing activation of stress pathways and cell death. We demonstrated that ERK and Akt signaling are activated by addition of as little as 10 μM extracellular Zn2+ (approximately 70 nM cytosolic labile Zn2+) and that these kinases are activated through a similar mechanism. We demonstrate that the upstream signaling proteins MEK and Ras are activated by Zn2+ addition, but that EGFR is not, thus honing in on Ras as a signaling node through which Zn2+ activates cell signaling pathways (Fig 7). The mechanism by which Ras is activated by Zn2+ remains elusive. Furthermore, the cell-type specificity of these signaling changes is not fully understood, and while we demonstrate that three different cell lines exhibit Zn2+-dependent ERK activation, there is still much to learn about whether certain cell systems respond to Zn2+ in unique ways.
This work provides context for understanding the origin and breadth of kinase activation in cells that experience physiological Zn2+ fluctuations. Much like Ca2+, defining how Zn2+ acts as a signaling ion is a critical step in determining how Zn2+ influences cell biology and understanding how disruptions in Zn2+ (deficiency or overdose) may impact cellular systems. This study provides a framework for Zn2+ manipulation in which cytosolic Zn2+ changes are quantified and correlated with signaling events in single cells. Our work suggests that targeting Ras signaling may be effective in systems that experience Zn2+ dysregulation and that broad non-specific phosphatase inhibition by Zn2+ is not a strong driver of Zn2+-dependent signaling changes when the Zn2+ perturbations don’t induce stress-response pathways. As the landscape of fluorescent biosensors and chemical probes expands, hopefully more pieces of this signaling pathway will fall into place and we will gain an even fuller understanding of the role Zn2+ plays in kinase signaling.
Author Contributions
K.J.A. and A.E.P. designed the study and wrote the manuscript. K.J.A. and G.A.C. collected data, and K.J.A. performed data analysis. All authors reviewed the manuscript.
Materials and Methods
Key Resources Table
(attached)
Molecular Cloning
pLentiCMV-Puro-DEST-ERKKTRClover and pLentiPGK-Blast-DEST-JNKKTRmRuby2 were purchased from Addgene (plasmid #59150 and 59154 respectively), and translocation sensor domains were subcloned into the pcDNA3.1-mCherry backbone to create mCherry fusions. KTR sequences were PCR amplified using primers listed in the resources table, with Nhe1 overhang on the forward primer and Age1 overhang on the reverse primer. Sensors were then cloned into pcDNA3.1-mCherry using restriction digest upstream of the mCherry fluorescent protein using restriction enzymes Nhe1 and Age1.
To generate ERKKTR-mCherry adenovirus for transduction of difficult-to-transfect cells, primers in the resources table were used to PCR amplify ERKKTR-mCherry out of the pcDNA3.1 backbone with overhangs matching the pShuttle recipient plasmid. This insert was then cloned into pShuttle using InFusion® HD Cloning Kit (Clontech/Takara) according to manufacturer’s instruction.
Mammalian Cell Culture
HeLa cells (ATCC CCL-2) were maintained in full growth DMEM supplemented with 10% bovine serum albumin, and 1% Pen/strep antibiotics. MCF10A cell line (ATCC) was maintained in full growth DMEM/F12 medium (FGM) supplemented with 5% horse serum, 1% Pen/strep antibiotics, 20 ng/mL EGF, 0.5 μg/ml hydrocortisone, 100 ng/ml cholera toxin, and 10 μg/ml insulin. The HT-22 cell line was obtained from Xuedong Liu Lab (University of Colorado Boulder) who obtained it as a gift from Toni Pak (Loyola University) and maintained in full growth DMEM supplemented with 10% bovine serum albumin, and 1% Pen/strep antibiotics. All cells were grown in a humidified incubator at 37°C and 5% CO2. Cells were passaged with trypsin-EDTA and routinely tested for mycoplasma.
HeLa cell lines expressing PB-NES ZapCV229 and/or PB-H2B-Halo65 were generated using the PiggyBac Transposon system via TransIT-LT1 (Mirus Bio) according to the manufacturer’s instructions. HeLa cell lines expressing pLenti-FoxO1-Clover were generated by transient transfection of HEK293T cells with pLenti-FoxO1-Clover and Lenti-X fourth-generation lentiviral packaging plasmids, pRev, pMDL, and pVSV-G (Takara Bio), followed by viral amplification in cells for 72 hours and addition of viral particles to HeLa cells. Stable cell lines used for imaging were generated by antibiotic selection (G418: PB-H2B-Halo, blasticidin: PB-NES-ZapCV2, puromycin: pLenti-FoxO1-Clover) followed by FACS enrichment for positive fluorescent cells. All transiently transfected sensors (pcDNA3.1-ERKKTR-mCherry, pcDNA3.1-JNKKTR-mCherry, pBSR-RaichuEV-Ras, pcDNA3.1-ZapCV5) were transfected using TransIT-LT1 per manufacturer’s instructions, and cells were imaged 48-72 hours post-transfection. MCF10A cells were transiently transduced via addition of adenovirus particles to cells at MOI = 10 (Adenovirus generation in Supplemental methods).
For imaging and growth experiments, cells were transferred to phosphate-free HEPES-buffered Hanks Balanced Salt Solution (HHBSS) buffer and incubated at 37°C and 0% CO2 for at least 30 minutes prior to imaging.
Live-cell imaging
For live imaging of cells stably expressing H2B-Halo, cells were incubated with 10 nM Halo-tagged Janelia Fluor 646 (JF646) dye (Janelia Research Campus) in phosphate-free HHBSS imaging media for 10 minutes at 37°C and 0% CO2. Cells were then washed twice and incubated in phosphate-free HHBSS at 37°C and 0% CO2 for 20-30 minutes prior to imaging. For imaging of cells without H2B-Halo tag (Fig 2), cells were instead incubated with 20 μg/mL Hoechst in phosphate-free HHBSS imaging media for 30 minutes at 37°C and 0% CO2, and cells were transferred into fresh phosphate-free HHBSS prior to imaging.
Fluorescence microscopy was performed on a Nikon Ti-E inverted microscope with a Lumencor SPECTRA X light engine (Lumencor, Beaverton, OR) and Hamamatsu Orca FLASH-4.0 V2 cMOS camera (Hamamatsu, Japan). Images were collected every 1, 2, or 5 minutes with a 20X 0.8 NA Plan Apo objective lens (Nikon Instruments, Melville, NY). Cells were kept in an environmental chamber surrounding the microscope (Okolab Cage Incubator, Okolab USA INC, San Bruno, CA) at 37°C, 0% CO2, and 90% humidity. Several ROIs in the same dish were imaged in a single cycle with light exposure of cells being 100 ms per timepoint at 50% LED light power. Filter sets used for live cell imaging were: CFP Ex: 440 Em: 460-500; GFP Ex: 470, Em: 500-545; YFP Ex: 508, Em: 520-550; CFPYFP FRET Ex: 440, Em: 520-550; mCherry Ex: 555, Em: 590-650; Cy5 Ex: 640, Em: 663-738.
Image Analysis
A diagram of our MATLAB image processing pipeline is in Supp Fig 4. Briefly, the Nikon ND2 image file is imported into MATLAB, cells are segmented by nuclear marker in either Cy5 (H2B-Halo + JF646) or BFP (Hoechst nuclear dye) channel, using the watershed method to generate nuclear masks. Automatic image registration happens at any pause in the experiment to account for small shifts of imaging dishes during media manipulation and nuclei are tracked throughout the experiment. A nuclear mask and cytosolic ring (4 pixels dilated from the nucleus) are generated and all channels are subjected to local background subtraction. Average intensity in the nucleus and cytosol of each cell is measured. Cells with very low or high sensor fluorescence were omitted, as well as cells that die during imaging, and cells that lose tracking during the course of the experiment. For a more detailed look at image processing, please see supplemental information in Lo et al., eLife, 202016.
Translocation sensors use the average cytosolic fluorescence divided by average nuclear fluorescence to yield a C/N Ratio. For FRET sensors, average intensity in the cytosol for the acceptor channel (CFP ex, YFP em) is divided by the average intensity for the donor channel (CFP) to yield a FRET ratio. YFP fluorescence is also tracked over time to monitor photobleaching. Normalization of each trace was performed by dividing the FRET or C/N ratio at each timepoint by the FRET or C/N ratio at the frame prior to Zn2+ or EGF addition to facilitate visualization of the changes resulting from perturbation. From this, the mean and standard error of the mean were taken for each sensor and plotted over time.
FRET Sensor Calibration
Zn2+ sensor calibrations were performed in phosphate-free HEPES-buffered HBSS, pH 7.4 (HHBSS), to prevent Zn2+ precipitation. To collect Rrest (rest, in Fig 1), cells were incubated in HHBSS for at least 30 minutes and then imaged for 10 minutes. Cells were then treated with either 10, 20, or 40 μM ZnCl2 for 30 minutes by adding 1 mL of 2X concentrated Zn2+ solutions in HHBSS to imaging dishes containing 1 mL HHBSS to get Rinflux (influx, in Fig 1). To collect Rapo (min, in Fig 1), 1 mL was removed from imaging dishes and 100 μM TPA in 1 mL HHBSS was added to cells (50 μM TPA final). After 8 minutes, cells were washed with HHBSS three times and two frames were imaged before adding Rmax solution of 81.6 μM buffered Zn2+ (Zn2+ buffered with the chelator EGTA and counter-ion CaCl2, Supp Table 2), 750 ⋂M pyrithione, and 0.002% saponin (added as 2X concentrated solution in 1 mL HHBSS). The average FRET ratio for rest was calculated by averaging across the timepoints collected, min FRET ratio was the minimum over the timeframe after TPA addition, and max FRET ratio was taken as the maximum FRET ratio over the timeframe after Zn2+ / pyrithione / saponin addition. To find FRET ratio max after Zn2+ influx, data from the timeframe after Zn2+ addition was fit to the equation y = a* e(−b*x) + c using the MATLAB curve fitting tool. Fit parameters in Supp Table S2.
To convert FRET ratios into approximate Zn2+ concentrations, the equations and were used, with each R value being the mean of each cell and Rinflux coming from the curve fit asymptote. ZapCV2: KD = 5.3 nM, Hill = 0.29 55; ZapCV5: KD = 300 nM, Hill = 0.55 29.
Cell Death Assay
To assess toxicity of Zn2+ treatment conditions, cells in a 96-well clear-bottom plate were incubated in HHBSS with a variety of Zn2+ or TPA conditions for 3.5 hours at 37°C and 0% CO2 and 30 minutes at room temperature. The four-hour timepoint was chosen to represent the longest possible time cells would be in HHBSS for imaging experiments, and each condition was represented by at least 6 individual wells. CelITiter-GIo® Luminescent Cell Viability Assay (Promega) was used to measure the average ATP content of each well, which is representative of the number of metabolically active cells. Cells were plated at equal density, and signal of each well was divided by average signal in background wells with no cells. The mean HHBSS signal was set as 1, and fraction alive was calculated for each individual well by dividing the well signal by mean HHBSS signal. A one-way ANOVA test comparing HHBSS control to each other experimental condition was conducted in MATLAB.
Kinase array
Proteome Profiler Human Phospho-Kinase Array Kit (R&D Systems) was used to measure changes in phosphorylation of 43 kinases upon 40 μM Zn2+ treatment. Cells were plated at equal density in 10 cm dishes, and cells were incubated in HHBSS for 30 min at 37°C and 0% CO2. Media was then replaced with HHBSS with and without 40 μM Zn2+ and further incubated at 37°C and 0% CO2 for 30 minutes. Cell lysis: cells were washed twice with cold PBS, then 900 uL RIPA buffer (150 mM NaCl, 1% Nonidet P-40, 0.5% deoxycholate, 0.1% SDS, 50 mM Tris pH 8.0, 5 mM EDTA) was added to each dish and cells were scraped into microfuge tube and rocked at 4°C for 30 minutes to lyse followed by centrifugation and collection of supernatant. Protein concentration was measured by Pierce™ BCA Protein Assay Kit (Thermo-Fisher), and 192 μg protein was used for each condition (2X HHBSS control, 2X 40 μM Zn2+).
Kinase array kits were used according to manufacturer’s recommendation. Briefly, membranes were blocked for an hour at room temp, then protein lysate was added and incubated at 4°C overnight. Membranes were washed three times before primary antibody cocktails were added and incubated for 2 hours at room temperature. Membranes were washed three times before addition of Streptavidin-HRP for 30 min at room temperature. Membranes were again washed three times, detection reagent was added, and membranes were imaged on an ImageQuant LAS4000 imaging system (GE Healthcare Life Sciences). Dot intensity data is in Supp Table S2.
Immunoblots
Cells in 6-well plates were incubated in HHBSS for 30 min at 37°C and 0% CO2, then media was replaced with HHBSS with indicated EGF and Zn2+ concentrations incubated 30 more minutes at 37°C and 0% CO2. Total cell lysates were collected with RIPA buffer (150 mM NaCl, 1% Nonidet P-40, 0.5% deoxycholate, 0.1% SDS, 50 mM Tris pH 8.0, 5 mM EDTA). Two wells of each 6-well plate were combined for each condition to have high enough protein concentration of immunoblotting. Proteins were separated using 10% SDS-PAGE gels and transferred to PVDF. Blots were blocked with 5% milk and probed with primary antibodies in the resources table. Secondary antibody Goat anti-Rabbit IgG [HRP] (Novus Biologicals) was reacted with Amersham ECL Prime Western Blotting Detection Reagent (Thomas Sci) and imaged on an ImageQuant LAS4000 imaging system (GE Healthcare Life Sciences). Antibody dilutions are reported in the Resource Table.
ERK Phosphatase Assay
To determine the impact of Zn2+ on ERK phosphatase activity in whole cell extracts, an ERK phosphatase assay was adapted from Levinthal and DeFranco, JBC, 200566. Six dishes of cells were transferred to phosphate-free HHBSS; one dish was treated with 40 μM ZnCl2 and one was treated with 5 μM TPA. After 30 minutes at 37°C and 0% CO2,100 μg protein from whole cell lysate was diluted into phosphatase assay buffer (10 mM MgCl2,10 mM HEPES pH 7.5, and 2 μM MEK inhibitor CI-1040); to samples of untreated cell lysate, 10 μM ZnCl2, 5 μM TPA, or 200 μM phosphatase inhibitor BCI-hydrochloride were added. For a positive control, 1200 units λ-protein phosphatase (NEB) were diluted into phosphatase assay buffer without cell lysate. 20 ng recombinant dual-phosphorylated His-ERK2 (generous gift from the lab of Dr. Natalie Ahn) was added to each sample and incubated at 37°C for 40 min. The reaction was stopped by adding 8 M urea, pH 8.6, with 10 mM imidazole, and 20 μL Ni-NTA beads were added to each sample to precipitate the His-tagged ERK. Samples were incubated for 90 min at 4°C. Samples were then washed twice in the urea / imidazole mixture and twice in 300 mM NaCl, 25 mM Tris, pH 7.5 buffer. Beads were then resuspended in 20 μL of the NaCI/Tris buffer + 25 μL 2X Laemmli Sample Buffer and boiled for 5 min. Samples were loaded onto a 4–20% Mini-PROTEAN® gradient polyacrylamide gel (Bio-Rad), transferred to PVDF, and blotted for total and phosphorylated ERK as above (in immunoblots section).
MKP3 Inhibition
To find IC50 of Zn2+ inhibition of MKP3/DUSP6, we performed an in-vitro plate-based fluorescence assay using recombinant human MKP-3 (Enzo Life Sciences) supplied in 20 mM Tris/HCl, pH 8.0, 200 mM NaCl, 5 mM DTT, 0.1% Tween-20, and 10% glycerol. Due to the Zn2+-chelating capacity of DTT67, the assay buffer we used contains TCEP as the reducing agent – 50 mM Tris/HCl, pH 7.4,100 mM NaCl, 100 μM TCEP, and 0.01% Tween-20. Methylumbelliferyl phosphate (MUP; Fisher Scientific), the fluorogenic phosphatase substrate (ex 386, em 448 nm), was diluted 1:10 into TCEP/Tween20 assay buffer and 110 μL was plated into each well of a 96-well glass-bottom plate. A variety of Zn2+ concentrations was added to the plate. Briefly, for trials 1 & 2, a dilution series of Zn2+ was used to establish Zn2+ concentrations ranging from 1-2500 μM and 1 nM −120 μM, respectively. For trial 3, a variety of Zn2+ chelators and counterions (Supp Table S3) were used to create a spectrum of buffered Zn2+ from 80 pM – 20 μM. Phosphatase inhibitor sodium orthovanadate, 1 mM, was used as a negative control. 250 nM MKP3 (10 μL volume added) was added to each well and the plate was immediately scanned for MUP fluorescence, with data points taken every 30 seconds for 40 minutes with 360-20 nm excitation and 450-30 nm emission. The fluorescence signal for each sample was fit via linear regression, and slope was used to approximate phosphatase activity with “no Zn2+” wells set at % activity = 1.
Acknowledgements
We would like to thank the following for financial support: NIH DP1 to A.E.P. (GM114863), NIH Molecular Biophysics Training Grant T32 to K.J.A. (GM065103) and NSF GRFP to K.J.A. (DGE1650115). We would like to acknowledge the BioFrontiers Institute Advanced Light Microscopy Core, where data analysis and microscope support was provided by Drs. Joseph Dragavon and Jian Tay, supported by the BioFrontiers Institute and the Howard Hughes Medical Institute. We would also like to acknowledge the University of Colorado Biochemistry Cell Culture Core Facility, especially Theresa Nahreini for providing resources and support for all our cell work. We would also like to thank Dr. Johannes Rudolph for assistance with in-vitro phosphatase inhibition assays and helpful discussions and Dr. Stephen Langers for helping us create adenoviral versions of our sensors. We would also like to acknowledge Dr. Natalie Ahn, Dr. Luke Lavis, and Dr. Xuedong Liu for their generous assistance with experimental materials.