The proverbial saying ‘you are what you eat’ perfectly summarizes the concept that our diet can influence both our mental and physical health. We know that foods that are good for the heart, such as nuts, oily fish and berries, are also good for the brain. We know too that vitamins and minerals are essential for overall good health. But is there any evidence that increasing your intake of specific vitamins or minerals could help boost your brain power?

While it might sound almost too good to be true, there is some evidence that this is the case for at least one mineral, magnesium. Studies in rodents have shown that adding magnesium supplements to food improves how well the animals perform on memory tasks. Both young and old animals benefit from additional magnesium. Even elderly rodents with a condition similar to Alzheimer’s disease show less memory loss when given magnesium supplements. But what about other species?

Wu et al. now show that magnesium supplements also boost memory performance in fruit flies. One group of flies was fed with standard cornmeal for several days, while the other group received cornmeal supplemented with magnesium. Both groups were then trained to associate an odor with a food reward. Flies that had received the extra magnesium showed better memory for the odor when tested 24 hours after training.

Wu et al. show that magnesium improves memory in the flies via a different mechanism to that reported previously for rodents. In rodents, magnesium increased levels of a receptor protein for a brain chemical called glutamate. In fruit flies, by contrast, the memory boost depended on a protein that transports magnesium out of neurons. Mutant flies that lacked this transporter showed memory impairments. Unlike normal flies, those without the transporter showed no memory improvement after eating magnesium-enriched food. The results suggest that the transporter may help adjust magnesium levels inside brain cells in response to neural activity.

Humans produce four variants of this magnesium transporter, each encoded by a different gene. One of these transporters has already been implicated in brain development. The findings of Wu et al. suggest that the transporters may also act in the adult brain to influence cognition. Further studies are needed to test whether targeting the magnesium transporter could ultimately hold promise for treating memory impairments.

Magnesium (Mg²⁺) plays a critical role in cellular metabolism and is considered to be an essential co-factor for more than 350 enzymes (Romani and Scarpa, 2000; Vink and Nechifor, 2011). As a result, alterations of Mg²⁺ homeostasis are associated with a broad range of clinical conditions, including those affecting the nervous system, such as glaucoma (DeToma et al., 2014), Parkinson’s disease (Hermosura et al., 2005; Hermosura and Garruto, 2007; Lin et al., 2014; Shindo et al., 2016), Alzheimer’s disease (Andrási et al., 2000; Andrási et al., 2005; Cilliler et al., 2007; Durlach et al., 1997; Glick, 1990; Lemke, 1995; Chui et al., 2011; Vural et al., 2010), anxiety (Sartori et al., 2012), depression (Whittle et al., 2011; Murck, 2002; Murck, 2013; Rasmussen et al., 1990; Ghafari et al., 2015), and intellectual disability (Arjona et al., 2014).

Perhaps surprisingly, increasing brain Mg²⁺ through diet can enhance neuronal plasticity and memory performance of young and aged rodents, measured in a variety of behavioral tasks (Slutsky et al., 2010; Landfield and Morgan, 1984; Mickley et al., 2013; Abumaria et al., 2013). In addition, elevated Mg²⁺ reduced cognitive deficits in a mouse model of Alzheimer’s disease (Li et al., 2013) and enhanced the extinction of fear memories (Abumaria et al., 2011). These apparently beneficial effects have led to the proposal that dietary Mg²⁺ may have therapeutic value for patients with a variety of memory-related problems (Billard, 2011).

Despite the large number of potential sites of Mg²⁺ action in the brain, the memory-enhancing property in rodents has largely been attributed to increases in hippocampal synaptic density and the activity of N-methyl-D-aspartate glutamate receptors (NMDARs). Extracellular Mg²⁺ blocks the channel pore of the NMDAR and thereby inhibits the passage of other ions (Mayer et al., 1984; Bekkers and Stevens, 1993; Jahr and Stevens, 1990; Nowak et al., 1984). Importantly, prior neuronal depolarization, driven by other transmitter receptors, is required to release the Mg²⁺ block on the NMDAR and permit glutamate-gated Ca²⁺ influx. The NMDAR therefore plays an important role in neuronal plasticity as a potential Hebbian coincidence detector. Acute elevation of extracellular Mg²⁺ concentration ([Mg²⁺]_e) within the physiological range (0.8–1.2 mM) can antagonize induction of NMDAR-dependent long-term potentiation (Dunwiddie and Lynch, 1979; Malenka et al., 1992; Malenka and Nicoll, 1993; Slutsky et al., 2004). In contrast, increasing [Mg²⁺]_e for several hours in neuronal cultures leads to enhancement of NMDAR mediated currents and facilitation of the expression of LTP (Slutsky et al., 2004). The enhancing effects of increased [Mg²⁺]_e were also observed in vivo in the brain of rats fed with Mg²⁺-L-threonate (Slutsky et al., 2010). Hippocampal neuronal circuits undergo homeostatic plasticity (Turrigiano, 2008) to accommodate the increased [Mg²⁺]_e by upregulating expression of NR2B subunit containing NMDARs (Slutsky et al., 2004; Slutsky et al., 2010). The higher density of hippocampal synapses with NR2B containing NMDARs are believed to compensate for the chronic increase in [Mg²⁺]_e by enhancing NMDAR currents during burst firing. In support of this model, mice that are genetically engineered to overexpress NR2B exhibit enhanced hippocampal LTP and behavioral memory (Tang et al., 1999).

Olfactory memory in Drosophila involves a heterosynaptic mechanism driven by reinforcing dopaminergic neurons, which results in presynaptic depression of cholinergic connections between odor-activated mushroom body (MB) Kenyon cells (KCs) and downstream mushroom body output neurons (MBONs) (Schwaerzel et al., 2003; Aso et al., 2010; Aso et al., 2012; Claridge-Chang et al., 2009; Burke et al., 2012; Liu et al., 2012; Plaçais et al., 2013; Owald et al., 2015; Hige et al., 2015; Barnstedt et al., 2016; Perisse et al., 2016; Aso et al., 2014; Owald and Waddell, 2015). In addition, olfactory information is conveyed to KCs by cholinergic transmission from olfactory projection neurons (Yasuyama et al., 2002; Leiss et al., 2009). Although it is conceivable that glutamate is delivered to the MB network via an as yet to be identified route, there is currently no obvious location for NMDAR-dependent plasticity in the known architecture of the cholinergic input or output layers (Barnstedt et al., 2016). The fly therefore provides a potential model to investigate other mechanisms through which dietary Mg²⁺ might enhance memory.

The reinforcing effects of dopamine depend on the Dop1R D1-type dopamine receptor (Kim et al., 2007; Qin et al., 2012; Handler et al., 2019), which is positively coupled with cAMP production (Tomchik and Davis, 2009; Boto et al., 2014). Moreover, early studies in Drosophila identified the dunce and rutabaga encoded cAMP phosphodiesterase and type I Ca^2+-stimulated adenylate cyclase, respectively, to be essential for olfactory memory (Dudai et al., 1976; Byers et al., 1981; Dudai and Zvi, 1984; Chen et al., 1986; Livingstone et al., 1984; Levin et al., 1992). Studies in mammalian cells have shown that hormones or agents that increase cellular cAMP level often elicit a significant Na⁺-dependent extrusion of Mg²⁺ into the extracellular space (Romani and Scarpa, 1990b; Romani and Scarpa, 1990a; Romani and Scarpa, 2000; Vink and Nechifor, 2011; Vormann and Günther, 1987). However, it is unclear whether Mg²⁺ extrusion plays any role in memory processing.

Here we demonstrate that Drosophila long-term memory (LTM) can be enhanced with dietary Mg²⁺ supplementation. We find that the unextended (uex) (Maeda, 1984; Coulthard et al., 2010) gene, which encodes a functional fly ortholog of the mammalian Cyclin M2 Mg²⁺-efflux transporter (CNNM) proteins, is critical for the memory enhancing property of Mg²⁺. UEX function in MB KCs is required for LTM and functional restoration of uex reveals the MB to be the key site of Mg²⁺-dependent memory enhancement. Chronically changing cAMP metabolism by introducing mutations in the dnc or rut genes alters the cellular localization of UEX. Moreover, mutating the conserved cyclic nucleotide-binding homology (CNBH) domain in UEX uncouples an essential role for uex from its function in memory. UEX-driven Mg²⁺ efflux is required for slow rhythmic maintenance of KC Mg²⁺ levels suggesting a potential role for Mg²⁺ flux in memory processing.

We observed an enhancement of olfactory LTM performance when flies were fed for 4 days before training with food supplemented with 80 mM [Mg²⁺]. This result resembles that reported in rats, although longer periods of feeding were required to raise brain [Mg²⁺] to memory-enhancing levels (Slutsky et al., 2010). A difference in optimal feeding time may reflect the size of the animal and perhaps the greater bioavailability of dietary Mg²⁺ in Drosophila. Whereas Mg²⁺-L-threonate (MgT) was a more effective means of delivering Mg²⁺ than magnesium chloride in rats (Slutsky et al., 2010), we observed a similar enhancement of memory performance when flies were fed with magnesium chloride, magnesium sulfate, or MgT (data not shown).

Elevating [Mg²⁺]_e in the rat brain leads to a compensatory upregulation of expression of the NR2B subunit of the NMDAR and therefore an increase in the proportion of postsynaptic NR2B-containing NMDARs. This class of NMDARs have a longer opening time (Chen et al., 1999; Erreger et al., 2005) suggesting that this switch in subunit composition represents a homeostatic plasticity mechanism (Turrigiano, 2008) to accommodate for the increased NMDAR block imposed by increasing [Mg²⁺]_e. Moreover, overexpression of NR2B in the mouse forebrain can enhance synaptic facilitation and learning and memory performance (Tang et al., 1999), supporting an increase in NR2B being an important factor in Mg²⁺-enhanced memory. However, even in the original in vitro study of Mg²⁺-enhanced synaptic plasticity (Slutsky et al., 2004), it was noted that NMDAR currents were insufficient to fully explain the observed changes.

Our NMDAR subunit loss-of-function studies in the Drosophila KCs did not impair regular or Mg²⁺-enhanced memory. Furthermore, we did not detect an obvious change in the levels of brain-wide expression of glutamate receptor subunits in Mg²⁺-fed flies. Although NMDAR activity has previously been implicated in Drosophila olfactory memory, the effects were mostly ascribed to function outside the MB (Xia et al., 2005; Wu et al., 2007). In addition, overexpressing Nmdar1 in all neurons, or specifically in all KCs, did not alter STM or LTM. Ectopic overexpression in the MB of an NMDAR^N631Q version, which cannot be blocked by Mg²⁺, impaired LTM (Miyashita et al., 2012). However, this mutation permits ligand-gated Ca²⁺ entry, without the need for correlated neuronal depolarization, which may perturb KC function in unexpected ways. It is perhaps most noteworthy that learning-relevant synaptic depression in the MB can be driven by dopaminergic teaching signals delivered to cholinergic output synapses from odor-responsive KCs to specific MBONs (Claridge-Chang et al., 2009; Aso et al., 2012; Burke et al., 2012; Liu et al., 2012; Owald et al., 2015; Hige et al., 2015; Barnstedt et al., 2016; Perisse et al., 2016; Aso et al., 2014; Owald and Waddell, 2015; Handler et al., 2019). It is conceivable that KCs receive glutamate, from a source yet to be identified, but there is currently no obvious place in the MB network for NMDAR-dependent plasticity. Evidence therefore suggests that normal and Mg²⁺-enhanced Drosophila LTM is independent of NMDAR signaling in KCs. In addition, our MagFRET measurements indicate that Mg²⁺ feeding also increases the [Mg²⁺]_i of αβ KCs by approximately 50 µM.

We identified a role for uex, the single fly ortholog of the evolutionarily conserved family of CNNM-type Mg²⁺ efflux transporters (Ishii et al., 2016). There are four distinct CNNM genes in mice and humans, five in C. elegans, and two in zebrafish (Ishii et al., 2016; Arjona et al., 2013). The uex locus produces four alternatively spliced mRNA transcripts, but all encode the same 834 aa protein. The precise role of CNNM proteins in Mg²⁺ transport is somewhat contentious (Funato et al., 2018a; Arjona and de Baaij, 2018; Funato et al., 2018b; Giménez-Mascarell et al., 2019). Some propose that CNNM proteins are direct Mg²⁺ transporters, whereas others favor that they function as sensors of intracellular Mg²⁺ concentration [Mg²⁺]_i and/or regulators of other Mg²⁺ transporters. We found that ectopic expression of Drosophila UEX enhances Mg²⁺ efflux in HEK293 cells and that endogenous UEX limits [Mg²⁺]_i in αβ KCs in the fly brain. Therefore, if UEX is not itself a Mg²⁺ transporter, it must be able to interact effectively with human Mg²⁺ efflux transporters and to influence Mg²⁺ extrusion in Drosophila. Since UEX is the only CNNM protein in the fly, it may serve all the roles of the four individual mammalian CNNMs. However, the ability of mouse CNNM2 to restore memory capacity to uex mutant flies suggests that the memory-relevant UEX function can be substituted by that of CNNM2.

Interestingly, none of the disease-relevant variants of CNNM2 were able to complement the memory defect of uex mutant flies. The CNNM2 T568I variant substitutes a single amino acid in the second CBS domain (Arjona et al., 2014). The oncogenic protein tyrosine phosphatases of the PRL (phosphatase of regenerating liver) family bind to the CBS domains of CNNM2 and CNNM3 and can inhibit their Mg²⁺ transport function (Hardy et al., 2015; Giménez-Mascarell et al., 2017; Zhang et al., 2017). It will therefore be of interest to test the role of the UEX CBS domains and whether fly PRL-1 regulates UEX activity.

RNA-seq analysis reveals that uex is strongly expressed in the larval and adult fly digestive tract and nervous systems, as well as the ovaries (Gelbart and Emmert, 2010; Croset et al., 2018; Davie et al., 2018) suggesting that many uex mutations will be pleiotropic. Our uexΔ allele, which deletes 272 amino acids (including part of the second CBS and the entire CNBH domain) from the UEX C-terminus, results in developmental lethality when homozygous, demonstrating that uex is an essential gene. Mammalian CNNM4 is localized to the basolateral membrane of intestinal epithelial cells (Yamazaki et al., 2013). There it is believed to function in transcellular Mg²⁺ transport by exchanging intracellular Mg²⁺ for extracellular Na⁺ following apical entry through TRPM7 channels. Lethality in Drosophila could therefore arise from an inability to absorb sufficient Mg²⁺ through the larval gut. However, neuronally restricted expression of uex^RNAiwith elav-GAL4 also results in larval lethality (data not shown), suggesting UEX has an additional role in early development of the nervous system, like CNNM2 in humans and zebrafish (Arjona et al., 2014; Accogli et al., 2019). Perhaps surprisingly, flies carrying homozygous or trans-heterozygous combinations of several hypomorphic uex alleles have defective appetitive and aversive memory performance, yet they seem otherwise unaffected.

Genetically engineering the uex locus to add a C-terminal HA tag to the UEX protein allowed us to localize its expression in the brain. Labeling is particularly prominent in all major classes of KCs. Restricting knockdown of uex expression to all αβ KCs of adult flies, or even just the αβ_c subset reproduced the LTM defect. The LTM impairment was evident if uex^RNAi expression in αβ neurons was restricted to adult flies, suggesting UEX has a more sustained role in neuronal physiology. In contrast, knocking down uex expression in either the αβ_s or α′β′ neurons did not impair LTM. Activity of α′β′ neurons is required after training to consolidate appetitive LTM (Krashes and Waddell, 2008), whereas αβ_c and αβ_s KC output, together and separately, is required for its expression (Krashes and Waddell, 2008; Perisse et al., 2013). Therefore, observing normal LTM performance in flies with uex loss-of-function in αβ_s and α′β′ neurons argues against a general deficiency of αβ neuronal function when manipulating uex.

Dietary Mg²⁺ could not enhance the defective LTM performance of flies that were constitutively uex mutant, or harbored αβ KC-restricted uex loss-of-function. However, expressing uex in the αβ KCs of uex mutant flies restored the ability of Mg²⁺ to enhance performance. Therefore, the αβ KCs are the cellular locus for Mg^2+-enhanced memory in the fly.

It perhaps seems counterintuitive that UEX-directed magnesium efflux is required in KCs to support the memory-enhancing effects of Mg²⁺ feeding, when dietary Mg²⁺ elevates KC [Mg²⁺]_i. At this stage, we can only speculate as to why this is the case. We assume that the brain and αβ KCs, in particular, have to adapt in a balanced way to the higher levels of intracellular and extracellular Mg²⁺ that result from dietary supplementation. Our live-imaging of KC [Mg²⁺]_i in wild-type and uex mutant brains suggests that UEX-directed efflux is likely to be an essential factor in the active, and perhaps stimulus-evoked, homeostatic maintenance of these elevated levels.

A number of mammalian cell-types extrude Mg²⁺ in a cAMP-dependent manner, a few minutes after being exposed to β-adrenergic stimulation (Romani and Scarpa, 2000; Vormann and Günther, 1987; Jakob et al., 1989; Romani and Scarpa, 1990b; Romani and Scarpa, 1990a; Vormann and Günther, 1987; Günther et al., 1990; Howarth et al., 1994). The presence of a CNBH domain suggests that UEX and CNNMs could be directly regulated by cAMP. We tested the importance of the CNBH by introducing an R622K amino acid substitution that should block cAMP binding in the UEX CNBH. This subtle mutation abolished the ability of the uex^R622K transgene to restore LTM performance to uex mutant flies. We also used CRISPR to mutate the CNBH in the native uex locus. Although deleting the CNBH from CNNM4 abolished Mg²⁺ efflux activity (Chen et al., 2018), flies homozygous for the uex^T626NRR lesion were viable, demonstrating that they retain a sufficient level of UEX function. However, these flies exhibited impaired immediate and long-term memory. In addition, the performance of uex^T626NRR flies could not be enhanced by Mg²⁺ feeding. These data demonstrate that an intact CNBH is a critical element of memory-relevant UEX function. Binding of clathrin adaptor proteins to the CNNM4 CNBH has been implicated in basolateral targeting (Hirata et al., 2014), suggesting that UEX^T626NRR might be inappropriately localized in KCs. Furthermore, KC expression of the CNNM2 E122K mutant variant, which retains residual function but has a trafficking defect (Arjona et al., 2014), did not restore the uex LTM defect.

Although it has been questioned whether the CNNM2/3 CNBH domains bind cyclic nucleotides (Chen et al., 2018), we found that FSK evoked an increase in αβ KC [Mg²⁺]_i that was sensitive to uex mutation, and that UEX::HA was mislocalized in rut²⁰⁸⁰ adenylate cyclase (Han et al., 1992) and dnc¹ phosphodiesterase (Dudai et al., 1976) learning defective mutant flies. Whereas UEX::HA label was evenly distributed in γ, αβ_c, and αβ_s KCs in wild-type flies, UEX::HA label was diminished in the γ and αβ_s KCs and was stronger in αβ_c neurons in rut²⁰⁸⁰ and dnc¹ mutants. The chronic manipulations of cAMP in the mutants are therefore consistent with cAMP impacting UEX localization, perhaps by interacting with the CNBH. In addition, altered UEX localization may contribute to the memory defects of rut²⁰⁸⁰ and dnc¹ flies.

Our physiological data using Magnesium Green in mammalian cell culture and the genetically encoded MagIC reporter in αβ KCs demonstrate that fly UEX facilitates Mg²⁺efflux. Stimulating the fly brain with FSK evoked a greater increase in αβ KC [Mg²⁺]_i in uex mutant brains than in wild-type controls which provides the first evidence that UEX limits a rise in [Mg²⁺]_i in Drosophila KCs. Our MagIC recordings also revealed a slow oscillation (centered around 0.015 Hz, approximately once a minute) of αβ KC [Mg²⁺]_i that was dependent on UEX. We do not yet understand the physiological function of this [Mg²⁺]_i fluctuation although it likely reflects a homeostatic systems-level property of the cells. Biochemical oscillatory activity plays a crucial role in many aspects of cellular physiology (Novák and Tyson, 2008). Most notably, circadian timed fluctuation of [Mg²⁺]_i links dynamic cellular energy metabolism to clock-controlled translation through the Mg²⁺ sensitive mTOR (mechanistic target of rapamycin) pathway (Feeney et al., 2016). It is therefore possible that slow Mg²⁺ oscillations could unite roles for cAMP, UEX, energy flux (Plaçais et al., 2017), and mTOR-dependent translation underlying LTM-relevant synaptic plasticity (Casadio et al., 1999; Huber et al., 2000; Beaumont et al., 2001; Hou and Klann, 2004; Hoeffer et al., 2008).

Behaviour data from T-maze assays are deposited in Dryad Digital Repository (https://doi.org/10.5061/dryad.q2bvq83hs). All other data generated or analysed during this study are included in the manuscript and supporting files.

1. 1. Wu Y
   2. Funato Y
   3. Meschi E
   4. Jovanoski KD
   5. Miki H
   6. Waddell S

   (2020) Dryad Digital Repository

   Behavior data from T-maze assay.

   https://doi.org/10.5061/dryad.q2bvq83hs
2. 1. Wu Y
   2. Funato Y
   3. Meschi E
   4. Jovanoski KD
   5. Miki H
   6. Waddell S

   (2020) Dryad Digital Repository

   Imaging data from ex-vivo MagIC assay Part II.

   https://doi.org/10.5061/dryad.zpc866t7d
3. 1. Wu Y
   2. Funato Y
   3. Meschi E
   4. Jovanoski KD
   5. Miki H
   6. Waddell S

   (2020) Dryad Digital Repository

   MagFRET signal from fixed brain.

   https://doi.org/10.5061/dryad.dv41ns1wp
4. 1. Wu Y
   2. Funato Y
   3. Meschi E
   4. Jovanoski KD
   5. Miki H
   6. Waddell S

   (2020) Dryad Digital Repository

   Imaging data from ex-vivo MagIC assay Part I.

   https://doi.org/10.5061/dryad.k0p2ngf6z
5. 1. Wu Y
   2. Funato Y
   3. Meschi E
   4. Jovanoski KD
   5. Miki H
   6. Waddell S

   (2020) Dryad Digital Repository

   Immuno-Fluorescence data from confocal scanning.

   https://doi.org/10.5061/dryad.80gb5mkpx

1. 1. Abumaria N
   2. Yin B
   3. Zhang L
   4. Li XY
   5. Chen T
   6. Descalzi G
   7. Zhao L
   8. Ahn M
   9. Luo L
   10. Ran C
   11. Zhuo M
   12. Liu G

   (2011) Effects of elevation of brain magnesium on fear conditioning, fear extinction, and synaptic plasticity in the infralimbic prefrontal cortex and lateral amygdala

   Journal of Neuroscience 31:14871–14881.

   https://doi.org/10.1523/JNEUROSCI.3782-11.2011

   • PubMed
   • Google Scholar
2. 1. Abumaria N
   2. Luo L
   3. Ahn M
   4. Liu G

   (2013) Magnesium supplement enhances spatial-context pattern separation and prevents fear overgeneralization

   Behavioural Pharmacology 24:255–263.

   https://doi.org/10.1097/FBP.0b013e32836357c7

   • PubMed
   • Google Scholar
3. 1. Accogli A
   2. Scala M
   3. Calcagno A
   4. Napoli F
   5. Di Iorgi N
   6. Arrigo S
   7. Mancardi MM
   8. Prato G
   9. Pisciotta L
   10. Nagel M
   11. Severino M
   12. Capra V

   (2019) CNNM2 homozygous mutations cause severe refractory hypomagnesemia, epileptic encephalopathy and brain malformations

   European Journal of Medical Genetics 62:198–203.

   https://doi.org/10.1016/j.ejmg.2018.07.014

   • PubMed
   • Google Scholar
4. 1. Andrási E
   2. Igaz S
   3. Molnár Z
   4. Makó S

   (2000)

   Disturbances of magnesium concentrations in various brain Areas in Alzheimer’s disease

   Magnesium Research 13:189–196.

   • PubMed
   • Google Scholar
5. 1. Andrási E
   2. Páli N
   3. Molnár Z
   4. Kösel S

   (2005) Brain aluminum, magnesium and phosphorus contents of control and Alzheimer-diseased patients

   Journal of Alzheimer's Disease 7:273–284.

   https://doi.org/10.3233/JAD-2005-7402

   • PubMed
   • Google Scholar
6. 1. Arcà B
   2. Zabalou S
   3. Loukeris TG
   4. Savakis C

   (1997)

   Mobilization of a Minos transposon in Drosophila melanogaster chromosomes and chromatid repair by heteroduplex formation

   Genetics 145:267–279.

   • PubMed
   • Google Scholar
7. 1. Arjona FJ
   2. Chen Y-X
   3. Flik G
   4. Bindels RJ
   5. Hoenderop JG

   (2013) Tissue-specific expression and in vivo regulation of zebrafish orthologues of mammalian genes related to symptomatic hypomagnesemia

   Pflügers Archiv - European Journal of Physiology 465:1409–1421.

   https://doi.org/10.1007/s00424-013-1275-3

   • Google Scholar
8. 1. Arjona FJ
   2. de Baaij JH
   3. Schlingmann KP
   4. Lameris AL
   5. van Wijk E
   6. Flik G
   7. Regele S
   8. Korenke GC
   9. Neophytou B
   10. Rust S
   11. Reintjes N
   12. Konrad M
   13. Bindels RJ
   14. Hoenderop JG

   (2014) CNNM2 mutations cause impaired brain development and seizures in patients with hypomagnesemia

   PLOS Genetics 10:e1004267.

   https://doi.org/10.1371/journal.pgen.1004267

   • PubMed
   • Google Scholar
9. 1. Arjona FJ
   2. de Baaij JHF

   (2018) CrossTalk opposing view: cnnm proteins are not Na⁺/Mg²⁺ exchangers but Mg²⁺ transport regulators playing a central role in transepithelial Mg²⁺ (re)absorption

   The Journal of Physiology 596:747–750.

   https://doi.org/10.1113/JP275249

   • PubMed
   • Google Scholar
10. 1. Aso Y
    2. Siwanowicz I
    3. Bräcker L
    4. Ito K
    5. Kitamoto T
    6. Tanimoto H

    (2010) Specific dopaminergic neurons for the formation of labile aversive memory

    Current Biology 20:1445–1451.

    https://doi.org/10.1016/j.cub.2010.06.048

    • PubMed
    • Google Scholar
11. 1. Aso Y
    2. Herb A
    3. Ogueta M
    4. Siwanowicz I
    5. Templier T
    6. Friedrich AB
    7. Ito K
    8. Scholz H
    9. Tanimoto H

    (2012) Three dopamine pathways induce aversive odor memories with different stability

    PLOS Genetics 8:e1002768.

    https://doi.org/10.1371/journal.pgen.1002768

    • PubMed
    • Google Scholar
12. 1. Aso Y
    2. Hattori D
    3. Yu Y
    4. Johnston RM
    5. Iyer NA
    6. Ngo TT
    7. Dionne H
    8. Abbott LF
    9. Axel R
    10. Tanimoto H
    11. Rubin GM

    (2014) The neuronal architecture of the mushroom body provides a logic for associative learning

    eLife 3:e04577.

    https://doi.org/10.7554/eLife.04577

    • PubMed
    • Google Scholar
13. 1. Attrill H
    2. Falls K
    3. Goodman JL
    4. Millburn GH
    5. Antonazzo G
    6. Rey AJ
    7. Marygold SJ
    8. FlyBase Consortium

    (2016) FlyBase: establishing a gene group resource for Drosophila melanogaster

    Nucleic Acids Research 44:D786–D792.

    https://doi.org/10.1093/nar/gkv1046

    • PubMed
    • Google Scholar
14. 1. Barnstedt O
    2. Owald D
    3. Felsenberg J
    4. Brain R
    5. Moszynski JP
    6. Talbot CB
    7. Perrat PN
    8. Waddell S

    (2016) Memory-relevant mushroom body output synapses are cholinergic

    Neuron 89:1237–1247.

    https://doi.org/10.1016/j.neuron.2016.02.015

    • PubMed
    • Google Scholar
15. 1. Bassett AR
    2. Tibbit C
    3. Ponting CP
    4. Liu JL

    (2013) Highly efficient targeted mutagenesis of Drosophila with the CRISPR/Cas9 system

    Cell Reports 4:220–228.

    https://doi.org/10.1016/j.celrep.2013.06.020

    • PubMed
    • Google Scholar
16. 1. Beaumont V
    2. Zhong N
    3. Fletcher R
    4. Froemke RC
    5. Zucker RS

    (2001) Phosphorylation and local presynaptic protein synthesis in calcium- and calcineurin-dependent induction of crayfish long-term facilitation

    Neuron 32:489–501.

    https://doi.org/10.1016/S0896-6273(01)00483-4

    • PubMed
    • Google Scholar
17. 1. Bekkers JM
    2. Stevens CF

    (1993) NMDA receptors at excitatory synapses in the hippocampus: test of a theory of magnesium block

    Neuroscience Letters 156:73–77.

    https://doi.org/10.1016/0304-3940(93)90443-O

    • PubMed
    • Google Scholar
18. 1. Bendat J
    2. Piersol A
    3. Saunders H

    (2000) Random data-analysis and measurement procedures

    Measurement Science and Technology 11:1825.

    https://doi.org/10.1088/0957-0233/11/12/702

    • Google Scholar
19. Book

    1. Billard JM

    (2011)

    Brain magnesium homeostasis as a target for reducing cognitive ageing

    In: Vink R, Nechifor M, editors. Magnesium and Alzheimer’s Disease. University of Adelaide Press. pp. 99–112.

    • Google Scholar
20. 1. Boto T
    2. Louis T
    3. Jindachomthong K
    4. Jalink K
    5. Tomchik SM

    (2014) Dopaminergic modulation of cAMP drives nonlinear plasticity across the Drosophila mushroom body lobes

    Current Biology 24:822–831.

    https://doi.org/10.1016/j.cub.2014.03.021

    • PubMed
    • Google Scholar
21. 1. Brand AH
    2. Perrimon N

    (1993)

    Targeted gene expression as a means of altering cell fates and generating dominant phenotypes

    Development 118:401–415.

    • PubMed
    • Google Scholar
22. 1. Bubis J
    2. Neitzel JJ
    3. Saraswat LD
    4. Taylor SS

    (1988)

    A point mutation abolishes binding of cAMP to site A in the regulatory subunit of cAMP-dependent protein kinase

    The Journal of Biological Chemistry 263:9668–9673.

    • PubMed
    • Google Scholar
23. 1. Burke CJ
    2. Huetteroth W
    3. Owald D
    4. Perisse E
    5. Krashes MJ
    6. Das G
    7. Gohl D
    8. Silies M
    9. Certel S
    10. Waddell S

    (2012) Layered reward signalling through octopamine and dopamine in Drosophila

    Nature 492:433–437.

    https://doi.org/10.1038/nature11614

    • PubMed
    • Google Scholar
24. 1. Byers D
    2. Davis RL
    3. Kiger JA

    (1981) Defect in cyclic AMP phosphodiesterase due to the dunce mutation of learning in Drosophila melanogaster

    Nature 289:79–81.

    https://doi.org/10.1038/289079a0

    • PubMed
    • Google Scholar
25. 1. Casadio A
    2. Martin KC
    3. Giustetto M
    4. Zhu H
    5. Chen M
    6. Bartsch D
    7. Bailey CH
    8. Kandel ER

    (1999) A transient, neuron-wide form of CREB-mediated long-term facilitation can be stabilized at specific synapses by local protein synthesis

    Cell 99:221–237.

    https://doi.org/10.1016/S0092-8674(00)81653-0

    • PubMed
    • Google Scholar
26. 1. Chen CN
    2. Denome S
    3. Davis RL

    (1986) Molecular analysis of cDNA clones and the corresponding genomic coding sequences of the Drosophila dunce+ gene, the structural gene for cAMP phosphodiesterase

    PNAS 83:9313–9317.

    https://doi.org/10.1073/pnas.83.24.9313

    • PubMed
    • Google Scholar
27. 1. Chen N
    2. Luo T
    3. Raymond LA

    (1999) Subtype-dependence of NMDA receptor channel open probability

    The Journal of Neuroscience 19:6844–6854.

    https://doi.org/10.1523/JNEUROSCI.19-16-06844.1999

    • PubMed
    • Google Scholar
28. 1. Chen TW
    2. Wardill TJ
    3. Sun Y
    4. Pulver SR
    5. Renninger SL
    6. Baohan A
    7. Schreiter ER
    8. Kerr RA
    9. Orger MB
    10. Jayaraman V
    11. Looger LL
    12. Svoboda K
    13. Kim DS

    (2013) Ultrasensitive fluorescent proteins for imaging neuronal activity

    Nature 499:295–300.

    https://doi.org/10.1038/nature12354

    • PubMed
    • Google Scholar
29. 1. Chen YS
    2. Kozlov G
    3. Fakih R
    4. Funato Y
    5. Miki H
    6. Gehring K

    (2018) The cyclic nucleotide–binding homology domain of the integral membrane protein CNNM mediates dimerization and is required for Mg²⁺ efflux activity

    Journal of Biological Chemistry 293:19998–20007.

    https://doi.org/10.1074/jbc.RA118.005672

    • Google Scholar
30. Book

    1. Chui D
    2. Chen Z
    3. Yu J
    4. Zhang H
    5. Wang W
    6. Son Y
    7. Yang H
    8. Liu Y

    (2011)

    Magnesium and Alzheimer’s disease

    In: Vink R, Nechifor M, editors. Magnesium in the Central Nervous System. University of Adelaide Press. pp. 239–250.

    • Google Scholar
31. 1. Cilliler AE
    2. Ozturk S
    3. Ozbakir S

    (2007) Serum magnesium level and clinical deterioration in Alzheimer's disease

    Gerontology 53:419–422.

    https://doi.org/10.1159/000110873

    • PubMed
    • Google Scholar
32. 1. Claridge-Chang A
    2. Roorda RD
    3. Vrontou E
    4. Sjulson L
    5. Li H
    6. Hirsh J
    7. Miesenböck G

    (2009) Writing memories with light-addressable reinforcement circuitry

    Cell 139:405–415.

    https://doi.org/10.1016/j.cell.2009.08.034

    • PubMed
    • Google Scholar
33. 1. Coulthard AB
    2. Alm C
    3. Cealiac I
    4. Sinclair DA
    5. Honda BM
    6. Rossi F
    7. Dimitri P
    8. Hilliker AJ

    (2010) Essential loci in centromeric heterochromatin of Drosophila melanogaster I: the right arm of chromosome 2

    Genetics 185:479–495.

    https://doi.org/10.1534/genetics.110.117259

    • PubMed
    • Google Scholar
34. 1. Croset V
    2. Treiber CD
    3. Waddell S

    (2018) Cellular diversity in the Drosophila midbrain revealed by single-cell transcriptomics

    eLife 7:e34550.

    https://doi.org/10.7554/eLife.34550

    • PubMed
    • Google Scholar
35. 1. Davie K
    2. Janssens J
    3. Koldere D
    4. De Waegeneer M
    5. Pech U
    6. Kreft Ł
    7. Aibar S
    8. Makhzami S
    9. Christiaens V
    10. Bravo González-Blas C
    11. Poovathingal S
    12. Hulselmans G
    13. Spanier KI
    14. Moerman T
    15. Vanspauwen B
    16. Geurs S
    17. Voet T
    18. Lammertyn J
    19. Thienpont B
    20. Liu S
    21. Konstantinides N
    22. Fiers M
    23. Verstreken P
    24. Aerts S

    (2018) A single-cell transcriptome atlas of the aging Drosophila brain

    Cell 174:982–998.

    https://doi.org/10.1016/j.cell.2018.05.057

    • PubMed
    • Google Scholar
36. 1. DeToma AS
    2. Dengler-Crish CM
    3. Deb A
    4. Braymer JJ
    5. Penner-Hahn JE
    6. van der Schyf CJ
    7. Lim MH
    8. Crish SD

    (2014) Abnormal metal levels in the primary visual pathway of the DBA/2J mouse model of glaucoma

    BioMetals 27:1291–1301.

    https://doi.org/10.1007/s10534-014-9790-z

    • PubMed
    • Google Scholar
37. 1. Dietzl G
    2. Chen D
    3. Schnorrer F
    4. Su KC
    5. Barinova Y
    6. Fellner M
    7. Gasser B
    8. Kinsey K
    9. Oppel S
    10. Scheiblauer S
    11. Couto A
    12. Marra V
    13. Keleman K
    14. Dickson BJ

    (2007) A genome-wide transgenic RNAi library for conditional gene inactivation in Drosophila

    Nature 448:151–156.

    https://doi.org/10.1038/nature05954

    • PubMed
    • Google Scholar
38. 1. Dudai Y
    2. Jan YN
    3. Byers D
    4. Quinn WG
    5. Benzer S

    (1976) Dunce, a mutant of Drosophila deficient in learning

    PNAS 73:1684–1688.

    https://doi.org/10.1073/pnas.73.5.1684

    • PubMed
    • Google Scholar
39. 1. Dudai Y
    2. Zvi S

    (1984) Adenylate cyclase in the Drosophila memory mutant rutabaga displays an altered Ca²⁺ sensitivity

    Neuroscience Letters 47:119–124.

    https://doi.org/10.1016/0304-3940(84)90416-6

    • PubMed
    • Google Scholar
40. 1. Dunwiddie TV
    2. Lynch G

    (1979) The relationship between extracellular calcium concentrations and the induction of hippocampal long-term potentiation

    Brain Research 169:103–110.

    https://doi.org/10.1016/0006-8993(79)90377-9

    • PubMed
    • Google Scholar
41. 1. Durlach J
    2. Bac P
    3. Durlach V
    4. Durlach A
    5. Bara M
    6. Guiet-Bara A

    (1997)

    Are age-related neurodegenerative diseases linked with various types of magnesium depletion?

    Magnesium Research 10:339–353.

    • PubMed
    • Google Scholar
42. 1. Erreger K
    2. Dravid SM
    3. Banke TG
    4. Wyllie DJ
    5. Traynelis SF

    (2005) Subunit-specific gating controls rat NR1/NR2A and NR1/NR2B NMDA channel kinetics and synaptic signalling profiles

    The Journal of Physiology 563:345–358.

    https://doi.org/10.1113/jphysiol.2004.080028

    • PubMed
    • Google Scholar
43. 1. Feeney KA
    2. Hansen LL
    3. Putker M
    4. Olivares-Yañez C
    5. Day J
    6. Eades LJ
    7. Larrondo LF
    8. Hoyle NP
    9. O'Neill JS
    10. van Ooijen G

    (2016) Daily magnesium fluxes regulate cellular timekeeping and energy balance

    Nature 532:375–379.

    https://doi.org/10.1038/nature17407

    • PubMed
    • Google Scholar
44. 1. Finn RD
    2. Attwood TK
    3. Babbitt PC
    4. Bateman A
    5. Bork P
    6. Bridge AJ
    7. Chang HY
    8. Dosztányi Z
    9. El-Gebali S
    10. Fraser M
    11. Gough J
    12. Haft D
    13. Holliday GL
    14. Huang H
    15. Huang X
    16. Letunic I
    17. Lopez R
    18. Lu S
    19. Marchler-Bauer A
    20. Mi H
    21. Mistry J
    22. Natale DA
    23. Necci M
    24. Nuka G
    25. Orengo CA
    26. Park Y
    27. Pesseat S
    28. Piovesan D
    29. Potter SC
    30. Rawlings ND
    31. Redaschi N
    32. Richardson L
    33. Rivoire C
    34. Sangrador-Vegas A
    35. Sigrist C
    36. Sillitoe I
    37. Smithers B
    38. Squizzato S
    39. Sutton G
    40. Thanki N
    41. Thomas PD
    42. Tosatto SC
    43. Wu CH
    44. Xenarios I
    45. Yeh LS
    46. Young SY
    47. Mitchell AL

    (2017) InterPro in 2017-beyond protein family and domain annotations

    Nucleic Acids Research 45:D190–D199.

    https://doi.org/10.1093/nar/gkw1107

    • PubMed
    • Google Scholar
45. 1. Flynn GE
    2. Black KD
    3. Islas LD
    4. Sankaran B
    5. Zagotta WN

    (2007) Structure and rearrangements in the carboxy-terminal region of SpIH channels

    Structure 15:671–682.

    https://doi.org/10.1016/j.str.2007.04.008

    • PubMed
    • Google Scholar
46. 1. Funato Y
    2. Furutani K
    3. Kurachi Y
    4. Miki H

    (2018a) CrossTalk proposal: CNNM proteins are Na⁺/Mg²⁺ exchangers playing a central role in transepithelial Mg²⁺ (re)absorption

    The Journal of Physiology 596:743–746.

    https://doi.org/10.1113/JP275248

    • PubMed
    • Google Scholar
47. 1. Funato Y
    2. Furutani K
    3. Kurachi Y
    4. Miki H

    (2018b) Rebuttal from Yosuke Funato, Kazuharu Furutani, Yoshihisa Kurachi and Hiroaki Miki

    The Journal of Physiology 596:751.

    https://doi.org/10.1113/JP275706

    • PubMed
    • Google Scholar
48. Report

    1. Gelbart WM
    2. Emmert DB

    (2010) FlyBase High Throughput Expression Pattern Data, a Database of Drosophila Genes & Genomes

    FlyBase analysis.

    https://flybase.org/reports/FBrf0212041.html

    • Google Scholar
49. 1. Ghafari M
    2. Whittle N
    3. Miklósi AG
    4. Kotlowski C
    5. Kotlowsky C
    6. Schmuckermair C
    7. Berger J
    8. Bennett KL
    9. Singewald N
    10. Lubec G

    (2015) Dietary magnesium restriction reduces amygdala-hypothalamic GluN1 receptor complex levels in mice

    Brain Structure and Function 220:2209–2221.

    https://doi.org/10.1007/s00429-014-0779-8

    • PubMed
    • Google Scholar
50. 1. Giménez-Mascarell P
    2. Oyenarte I
    3. Hardy S
    4. Breiderhoff T
    5. Stuiver M
    6. Kostantin E
    7. Diercks T
    8. Pey AL
    9. Ereño-Orbea J
    10. Martínez-Chantar ML
    11. Khalaf-Nazzal R
    12. Claverie-Martin F
    13. Müller D
    14. Tremblay ML
    15. Martínez-Cruz LA

    (2017) Structural basis of the oncogenic interaction of phosphatase PRL-1 with the magnesium transporter CNNM2

    Journal of Biological Chemistry 292:786–801.

    https://doi.org/10.1074/jbc.M116.759944

    • Google Scholar
51. 1. Giménez-Mascarell P
    2. González-Recio I
    3. Fernández-Rodríguez C
    4. Oyenarte I
    5. Müller D
    6. Martínez-Chantar M
    7. Martínez-Cruz L

    (2019) Current structural knowledge on the CNNM family of magnesium transport mediators

    International Journal of Molecular Sciences 20:1135.

    https://doi.org/10.3390/ijms20051135

    • Google Scholar
52. 1. Glick JL

    (1990) Dementias: the role of magnesium deficiency and an hypothesis concerning the pathogenesis of Alzheimer's disease

    Medical Hypotheses 31:211–225.

    https://doi.org/10.1016/0306-9877(90)90095-V

    • PubMed
    • Google Scholar
53. 1. Gohl DM
    2. Silies MA
    3. Gao XJ
    4. Bhalerao S
    5. Luongo FJ
    6. Lin CC
    7. Potter CJ
    8. Clandinin TR

    (2011) A versatile in vivo system for directed dissection of gene expression patterns

    Nature Methods 8:231–237.

    https://doi.org/10.1038/nmeth.1561

    • PubMed
    • Google Scholar
54. 1. Gratz SJ
    2. Cummings AM
    3. Nguyen JN
    4. Hamm DC
    5. Donohue LK
    6. Harrison MM
    7. Wildonger J
    8. O'Connor-Giles KM

    (2013) Genome engineering of Drosophila with the CRISPR RNA-guided Cas9 nuclease

    Genetics 194:1029–1035.

    https://doi.org/10.1534/genetics.113.152710

    • PubMed
    • Google Scholar
55. 1. Günther T
    2. Vormann J
    3. Höllriegl V

    (1990) Characterization of Na+-dependent Mg2+ efflux from Mg²⁺-loaded rat erythrocytes

    Biochimica et Biophysica Acta (BBA) - Biomembranes 1023:455–461.

    https://doi.org/10.1016/0005-2736(90)90139-F

    • Google Scholar
56. 1. Han PL
    2. Levin LR
    3. Reed RR
    4. Davis RL

    (1992) Preferential expression of the Drosophila rutabaga gene in mushroom bodies, neural centers for learning in insects

    Neuron 9:619–627.

    https://doi.org/10.1016/0896-6273(92)90026-A

    • PubMed
    • Google Scholar
57. 1. Handler A
    2. Graham TGW
    3. Cohn R
    4. Morantte I
    5. Siliciano AF
    6. Zeng J
    7. Li Y
    8. Ruta V

    (2019) Distinct dopamine receptor pathways underlie the temporal sensitivity of associative learning

    Cell 178:60–75.

    https://doi.org/10.1016/j.cell.2019.05.040

    • PubMed
    • Google Scholar
58. 1. Hardy S
    2. Uetani N
    3. Wong N
    4. Kostantin E
    5. Labbé DP
    6. Bégin LR
    7. Mes-Masson A
    8. Miranda-Saavedra D
    9. Tremblay ML

    (2015) The protein tyrosine phosphatase PRL-2 interacts with the magnesium transporter CNNM3 to promote oncogenesis

    Oncogene 34:986–995.

    https://doi.org/10.1038/onc.2014.33

    • PubMed
    • Google Scholar
59. 1. Hermosura MC
    2. Nayakanti H
    3. Dorovkov MV
    4. Calderon FR
    5. Ryazanov AG
    6. Haymer DS
    7. Garruto RM

    (2005) A TRPM7 variant shows altered sensitivity to magnesium that may contribute to the pathogenesis of two guamanian neurodegenerative disorders

    PNAS 102:11510–11515.

    https://doi.org/10.1073/pnas.0505149102

    • PubMed
    • Google Scholar
60. 1. Hermosura MC
    2. Garruto RM

    (2007) TRPM7 and TRPM2—Candidate susceptibility genes for Western Pacific ALS and PD?

    Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 1772:822–835.

    https://doi.org/10.1016/j.bbadis.2007.02.008

    • Google Scholar
61. 1. Hige T
    2. Aso Y
    3. Modi MN
    4. Rubin GM
    5. Turner GC

    (2015) Heterosynaptic plasticity underlies aversive olfactory learning in Drosophila

    Neuron 88:985–998.

    https://doi.org/10.1016/j.neuron.2015.11.003

    • PubMed
    • Google Scholar
62. 1. Hirano Y
    2. Masuda T
    3. Naganos S
    4. Matsuno M
    5. Ueno K
    6. Miyashita T
    7. Horiuchi J
    8. Saitoe M

    (2013) Fasting launches CRTC to facilitate long-term memory formation in Drosophila

    Science 339:443–446.

    https://doi.org/10.1126/science.1227170

    • PubMed
    • Google Scholar
63. 1. Hirata Y
    2. Funato Y
    3. Miki H

    (2014) Basolateral sorting of the Mg²⁺ transporter CNNM4 requires interaction with AP-1A and AP-1B

    Biochemical and Biophysical Research Communications 455:184–189.

    https://doi.org/10.1016/j.bbrc.2014.10.138

    • PubMed
    • Google Scholar
64. 1. Hoeffer CA
    2. Tang W
    3. Wong H
    4. Santillan A
    5. Patterson RJ
    6. Martinez LA
    7. Tejada-Simon MV
    8. Paylor R
    9. Hamilton SL
    10. Klann E

    (2008) Removal of FKBP12 enhances mTOR-Raptor interactions, LTP, memory, and perseverative/repetitive behavior

    Neuron 60:832–845.

    https://doi.org/10.1016/j.neuron.2008.09.037

    • PubMed
    • Google Scholar
65. 1. Hou L
    2. Klann E

    (2004) Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required for metabotropic glutamate receptor-dependent long-term depression

    Journal of Neuroscience 24:6352–6361.

    https://doi.org/10.1523/JNEUROSCI.0995-04.2004

    • PubMed
    • Google Scholar
66. 1. Howarth FC
    2. Waring J
    3. Hustler BI
    4. Singh J

    (1994)

    Effects of extracellular magnesium and beta adrenergic stimulation on contractile force and magnesium mobilization in the isolated rat heart

    Magnesium Research 7:187–197.

    • PubMed
    • Google Scholar
67. 1. Huber KM
    2. Kayser MS
    3. Bear MF

    (2000) Role for rapid dendritic protein synthesis in hippocampal mGluR-dependent long-term depression

    Science 288:1254–1256.

    https://doi.org/10.1126/science.288.5469.1254

    • PubMed
    • Google Scholar
68. 1. Ishii T
    2. Funato Y
    3. Hashizume O
    4. Yamazaki D
    5. Hirata Y
    6. Nishiwaki K
    7. Kono N
    8. Arai H
    9. Miki H

    (2016) Mg2+ extrusion from intestinal epithelia by CNNM proteins is essential for gonadogenesis via AMPK-TORC1 signaling in Caenorhabditis elegans

    PLOS Genetics 12:e1006276.

    https://doi.org/10.1371/journal.pgen.1006276

    • PubMed
    • Google Scholar
69. 1. Jacob PF
    2. Waddell S

    (2020) Spaced training forms complementary long-term memories of opposite valence in Drosophila

    Neuron 106:977–991.

    https://doi.org/10.1016/j.neuron.2020.03.013

    • PubMed
    • Google Scholar
70. 1. Jahr CE
    2. Stevens CF

    (1990) Voltage dependence of NMDA-activated macroscopic conductances predicted by single-channel kinetics

    The Journal of Neuroscience 10:3178–3182.

    https://doi.org/10.1523/JNEUROSCI.10-09-03178.1990

    • PubMed
    • Google Scholar
71. 1. Jakob A
    2. Becker J
    3. Schöttli G
    4. Fritzsch G

    (1989) α1-adrenergic stimulation causes Mg²⁺ release from perfused rat liver

    FEBS Letters 246:127–130.

    https://doi.org/10.1016/0014-5793(89)80267-4

    • PubMed
    • Google Scholar
72. 1. Jones P
    2. Binns D
    3. Chang HY
    4. Fraser M
    5. Li W
    6. McAnulla C
    7. McWilliam H
    8. Maslen J
    9. Mitchell A
    10. Nuka G
    11. Pesseat S
    12. Quinn AF
    13. Sangrador-Vegas A
    14. Scheremetjew M
    15. Yong SY
    16. Lopez R
    17. Hunter S

    (2014) InterProScan 5: genome-scale protein function classification

    Bioinformatics 30:1236–1240.

    https://doi.org/10.1093/bioinformatics/btu031

    • PubMed
    • Google Scholar
73. 1. Kandel ER

    (2012) The molecular biology of memory: camp, PKA, CRE, CREB-1, CREB-2, and CPEB

    Molecular Brain 5:14.

    https://doi.org/10.1186/1756-6606-5-14

    • PubMed
    • Google Scholar
74. 1. Keene AC
    2. Stratmann M
    3. Keller A
    4. Perrat PN
    5. Vosshall LB
    6. Waddell S

    (2004) Diverse odor-conditioned memories require uniquely timed dorsal paired medial neuron output

    Neuron 44:521–533.

    https://doi.org/10.1016/j.neuron.2004.10.006

    • PubMed
    • Google Scholar
75. 1. Keene AC
    2. Krashes MJ
    3. Leung B
    4. Bernard JA
    5. Waddell S

    (2006) Drosophila dorsal paired medial neurons provide a general mechanism for memory consolidation

    Current Biology 16:1524–1530.

    https://doi.org/10.1016/j.cub.2006.06.022

    • PubMed
    • Google Scholar
76. 1. Kelley LA
    2. Mezulis S
    3. Yates CM
    4. Wass MN
    5. Sternberg MJ

    (2015) The Phyre2 web portal for protein modeling, prediction and analysis

    Nature Protocols 10:845–858.

    https://doi.org/10.1038/nprot.2015.053

    • PubMed
    • Google Scholar
77. 1. Kesters D
    2. Brams M
    3. Nys M
    4. Wijckmans E
    5. Spurny R
    6. Voets T
    7. Tytgat J
    8. Kusch J
    9. Ulens C

    (2015) Structure of the SthK carboxy-terminal region reveals a gating mechanism for cyclic nucleotide-modulated ion channels

    PLOS ONE 10:e0116369.

    https://doi.org/10.1371/journal.pone.0116369

    • PubMed
    • Google Scholar
78. 1. Kim YC
    2. Lee HG
    3. Han KA

    (2007) D1 dopamine receptor dDA1 is required in the mushroom body neurons for aversive and appetitive learning in Drosophila

    Journal of Neuroscience 27:7640–7647.

    https://doi.org/10.1523/JNEUROSCI.1167-07.2007

    • PubMed
    • Google Scholar
79. 1. Koldenkova VP
    2. Matsuda T
    3. Nagai T

    (2015) MagIC, a genetically encoded fluorescent indicator for monitoring cellular Mg²⁺ using a non-Förster resonance energy transfer ratiometric imaging approach

    Journal of Biomedical Optics 20:101203.

    https://doi.org/10.1117/1.JBO.20.10.101203

    • PubMed
    • Google Scholar
80. 1. Krashes MJ
    2. Keene AC
    3. Leung B
    4. Armstrong JD
    5. Waddell S

    (2007) Sequential use of mushroom body neuron subsets during Drosophila odor memory processing

    Neuron 53:103–115.

    https://doi.org/10.1016/j.neuron.2006.11.021

    • PubMed
    • Google Scholar
81. 1. Krashes MJ
    2. Waddell S

    (2008) Rapid consolidation to a radish and protein synthesis-dependent long-term memory after single-session appetitive olfactory conditioning in Drosophila

    Journal of Neuroscience 28:3103–3113.

    https://doi.org/10.1523/JNEUROSCI.5333-07.2008

    • PubMed
    • Google Scholar
82. 1. Kvon EZ
    2. Kazmar T
    3. Stampfel G
    4. Yáñez-Cuna JO
    5. Pagani M
    6. Schernhuber K
    7. Dickson BJ
    8. Stark A

    (2014) Genome-scale functional characterization of Drosophila developmental enhancers in vivo

    Nature 512:91–95.

    https://doi.org/10.1038/nature13395

    • PubMed
    • Google Scholar
83. 1. Landfield PW
    2. Morgan GA

    (1984) Chronically elevating plasma Mg²⁺ improves hippocampal frequency potentiation and reversal learning in aged and young rats

    Brain Research 322:167–171.

    https://doi.org/10.1016/0006-8993(84)91199-5

    • PubMed
    • Google Scholar
84. 1. Laurent G
    2. Naraghi M

    (1994) Odorant-induced oscillations in the mushroom bodies of the locust

    The Journal of Neuroscience 14:2993–3004.

    https://doi.org/10.1523/JNEUROSCI.14-05-02993.1994

    • PubMed
    • Google Scholar
85. 1. Leiss F
    2. Groh C
    3. Butcher NJ
    4. Meinertzhagen IA
    5. Tavosanis G

    (2009) Synaptic organization in the adult Drosophila mushroom body calyx

    The Journal of Comparative Neurology 517:808–824.

    https://doi.org/10.1002/cne.22184

    • PubMed
    • Google Scholar
86. 1. Lemke MR

    (1995) Plasma magnesium decrease and altered calcium/magnesium ratio in severe dementia of the Alzheimer type

    Biological Psychiatry 37:341–343.

    https://doi.org/10.1016/0006-3223(94)00241-T

    • Google Scholar
87. 1. Levin LR
    2. Han PL
    3. Hwang PM
    4. Feinstein PG
    5. Davis RL
    6. Reed RR

    (1992) The Drosophila learning and memory gene rutabaga encodes a Ca²⁺/Calmodulin-responsive adenylyl cyclase

    Cell 68:479–489.

    https://doi.org/10.1016/0092-8674(92)90185-F

    • PubMed
    • Google Scholar
88. 1. Li W
    2. Yu J
    3. Liu Y
    4. Huang X
    5. Abumaria N
    6. Zhu Y
    7. Huang X
    8. Xiong W
    9. Ren C
    10. Liu XG
    11. Chui D
    12. Liu G

    (2013) Elevation of brain magnesium prevents and reverses cognitive deficits and synaptic loss in Alzheimer's disease mouse model

    Journal of Neuroscience 33:8423–8441.

    https://doi.org/10.1523/JNEUROSCI.4610-12.2013

    • PubMed
    • Google Scholar
89. 1. Lin CH
    2. Wu YR
    3. Chen WL
    4. Wang HC
    5. Lee CM
    6. Lee-Chen GJ
    7. Chen CM

    (2014) Variant R244H in Na⁺/Mg²⁺ exchanger SLC41A1 in Taiwanese Parkinson’s disease is associated with loss of Mg²⁺ efflux function

    Parkinsonism & Related Disorders 20:600–603.

    https://doi.org/10.1016/j.parkreldis.2014.02.027

    • PubMed
    • Google Scholar
90. 1. Lindenburg LH
    2. Vinkenborg JL
    3. Oortwijn J
    4. Aper SJ
    5. Merkx M

    (2013) MagFRET: the first genetically encoded fluorescent Mg²⁺ sensor

    PLOS ONE 8:e82009.

    https://doi.org/10.1371/journal.pone.0082009

    • PubMed
    • Google Scholar
91. 1. Liu C
    2. Plaçais PY
    3. Yamagata N
    4. Pfeiffer BD
    5. Aso Y
    6. Friedrich AB
    7. Siwanowicz I
    8. Rubin GM
    9. Preat T
    10. Tanimoto H

    (2012) A subset of dopamine neurons signals reward for odour memory in Drosophila

    Nature 488:512–516.

    https://doi.org/10.1038/nature11304

    • PubMed
    • Google Scholar
92. 1. Livak KJ
    2. Schmittgen TD

    (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta delta C(T)) Method

    Methods 25:402–408.

    https://doi.org/10.1006/meth.2001.1262

    • PubMed
    • Google Scholar
93. 1. Livingstone MS
    2. Sziber PP
    3. Quinn WG

    (1984) Loss of calcium/calmodulin responsiveness in adenylate cyclase of rutabaga, a Drosophila learning mutant

    Cell 37:205–215.

    https://doi.org/10.1016/0092-8674(84)90316-7

    • PubMed
    • Google Scholar
94. 1. Louis T
    2. Stahl A
    3. Boto T
    4. Tomchik SM

    (2018) Cyclic AMP-dependent plasticity underlies rapid changes in odor coding associated with reward learning

    PNAS 115:E448–E457.

    https://doi.org/10.1073/pnas.1709037115

    • PubMed
    • Google Scholar
95. 1. Maeda Y

    (1984) Studies on the unextended (uex) mutant of Drosophila melanogaster

    The Japanese Journal of Genetics 59:249–257.

    https://doi.org/10.1266/jjg.59.249

    • Google Scholar
96. 1. Maeshima K
    2. Matsuda T
    3. Shindo Y
    4. Imamura H
    5. Tamura S
    6. Imai R
    7. Kawakami S
    8. Nagashima R
    9. Soga T
    10. Noji H
    11. Oka K
    12. Nagai T

    (2018) A transient rise in free Mg²⁺ ions released from ATP-Mg hydrolysis contributes to mitotic chromosome condensation

    Current Biology 28:444–451.

    https://doi.org/10.1016/j.cub.2017.12.035

    • PubMed
    • Google Scholar
97. 1. Malenka RC
    2. Lancaster B
    3. Zucker RS

    (1992) Temporal limits on the rise in postsynaptic calcium required for the induction of long-term potentiation

    Neuron 9:121–128.

    https://doi.org/10.1016/0896-6273(92)90227-5

    • PubMed
    • Google Scholar
98. 1. Malenka RC
    2. Nicoll RA

    (1993) NMDA-receptor-dependent synaptic plasticity: multiple forms and mechanisms

    Trends in Neurosciences 16:521–527.

    https://doi.org/10.1016/0166-2236(93)90197-T

    • PubMed
    • Google Scholar
99. 1. Mayer ML
    2. Westbrook GL
    3. Guthrie PB

    (1984) Voltage-dependent block by Mg²⁺ of NMDA responses in spinal cord neurones

    Nature 309:261–263.

    https://doi.org/10.1038/309261a0

    • PubMed
    • Google Scholar
100. 1. McGuire SE
     2. Le PT
     3. Davis RL

     (2001) The role of Drosophila mushroom body signaling in olfactory memory

     Science 293:1330–1333.

     https://doi.org/10.1126/science.1062622

     • PubMed
     • Google Scholar
101. 1. McGuire SE
     2. Le PT
     3. Osborn AJ
     4. Matsumoto K
     5. Davis RL

     (2003) Spatiotemporal rescue of memory dysfunction in Drosophila

     Science 302:1765–1768.

     https://doi.org/10.1126/science.1089035

     • PubMed
     • Google Scholar
102. 1. Mickley GA
     2. Hoxha N
     3. Luchsinger JL
     4. Rogers MM
     5. Wiles NR

     (2013) Chronic dietary magnesium-L-threonate speeds extinction and reduces spontaneous recovery of a conditioned taste aversion

     Pharmacology Biochemistry and Behavior 106:16–26.

     https://doi.org/10.1016/j.pbb.2013.02.019

     • PubMed
     • Google Scholar
103. 1. Miyashita T
     2. Oda Y
     3. Horiuchi J
     4. Yin JC
     5. Morimoto T
     6. Saitoe M

     (2012) Mg²⁺ block of Drosophila NMDA receptors is required for long-term memory formation and CREB-dependent gene expression

     Neuron 74:887–898.

     https://doi.org/10.1016/j.neuron.2012.03.039

     • PubMed
     • Google Scholar
104. 1. Murck H

     (2002) Magnesium and affective disorders

     Nutritional Neuroscience 5:375–389.

     https://doi.org/10.1080/1028415021000039194

     • PubMed
     • Google Scholar
105. 1. Murck H

     (2013) Ketamine, magnesium and major depression—from pharmacology to pathophysiology and back

     Journal of Psychiatric Research 47:955–965.

     https://doi.org/10.1016/j.jpsychires.2013.02.015

     • PubMed
     • Google Scholar
106. 1. Novák B
     2. Tyson JJ

     (2008) Design principles of biochemical oscillators

     Nature Reviews Molecular Cell Biology 9:981–991.

     https://doi.org/10.1038/nrm2530

     • PubMed
     • Google Scholar
107. 1. Nowak L
     2. Bregestovski P
     3. Ascher P
     4. Herbet A
     5. Prochiantz A

     (1984) Magnesium gates glutamate-activated channels in mouse central neurones

     Nature 307:462–465.

     https://doi.org/10.1038/307462a0

     • PubMed
     • Google Scholar
108. 1. Owald D
     2. Felsenberg J
     3. Talbot CB
     4. Das G
     5. Perisse E
     6. Huetteroth W
     7. Waddell S

     (2015) Activity of defined mushroom body output neurons underlies learned olfactory behavior in Drosophila

     Neuron 86:417–427.

     https://doi.org/10.1016/j.neuron.2015.03.025

     • PubMed
     • Google Scholar
109. 1. Owald D
     2. Waddell S

     (2015) Olfactory learning skews mushroom body output pathways to steer behavioral choice in Drosophila

     Current Opinion in Neurobiology 35:178–184.

     https://doi.org/10.1016/j.conb.2015.10.002

     • PubMed
     • Google Scholar
110. 1. Pascual A
     2. Préat T

     (2001) Localization of long-term memory within the Drosophila mushroom body

     Science 294:1115–1117.

     https://doi.org/10.1126/science.1064200

     • PubMed
     • Google Scholar
111. 1. Perisse E
     2. Yin Y
     3. Lin AC
     4. Lin S
     5. Huetteroth W
     6. Waddell S

     (2013) Different Kenyon cell populations drive learned approach and avoidance in Drosophila

     Neuron 79:945–956.

     https://doi.org/10.1016/j.neuron.2013.07.045

     • PubMed
     • Google Scholar
112. 1. Perisse E
     2. Owald D
     3. Barnstedt O
     4. Talbot CB
     5. Huetteroth W
     6. Waddell S

     (2016) Aversive learning and appetitive motivation toggle feed-forward inhibition in the Drosophila mushroom body

     Neuron 90:1086–1099.

     https://doi.org/10.1016/j.neuron.2016.04.034

     • PubMed
     • Google Scholar
113. 1. Perkins LA
     2. Holderbaum L
     3. Tao R
     4. Hu Y
     5. Sopko R
     6. McCall K
     7. Yang-Zhou D
     8. Flockhart I
     9. Binari R
     10. Shim HS
     11. Miller A
     12. Housden A
     13. Foos M
     14. Randkelv S
     15. Kelley C
     16. Namgyal P
     17. Villalta C
     18. Liu LP
     19. Jiang X
     20. Huan-Huan Q
     21. Wang X
     22. Fujiyama A
     23. Toyoda A
     24. Ayers K
     25. Blum A
     26. Czech B
     27. Neumuller R
     28. Yan D
     29. Cavallaro A
     30. Hibbard K
     31. Hall D
     32. Cooley L
     33. Hannon GJ
     34. Lehmann R
     35. Parks A
     36. Mohr SE
     37. Ueda R
     38. Kondo S
     39. Ni JQ
     40. Perrimon N

     (2015) The transgenic RNAi project at Harvard medical school: resources and validation

     Genetics 201:843–852.

     https://doi.org/10.1534/genetics.115.180208

     • PubMed
     • Google Scholar
114. 1. Pettersen EF
     2. Goddard TD
     3. Huang CC
     4. Couch GS
     5. Greenblatt DM
     6. Meng EC
     7. Ferrin TE

     (2004) UCSF chimera--a visualization system for exploratory research and analysis

     Journal of Computational Chemistry 25:1605–1612.

     https://doi.org/10.1002/jcc.20084

     • PubMed
     • Google Scholar
115. 1. Plaçais PY
     2. Trannoy S
     3. Friedrich AB
     4. Tanimoto H
     5. Preat T

     (2013) Two pairs of mushroom body efferent neurons are required for appetitive long-term memory retrieval in Drosophila

     Cell Reports 5:769–780.

     https://doi.org/10.1016/j.celrep.2013.09.032

     • PubMed
     • Google Scholar
116. 1. Plaçais PY
     2. de Tredern É
     3. Scheunemann L
     4. Trannoy S
     5. Goguel V
     6. Han KA
     7. Isabel G
     8. Preat T

     (2017) Upregulated energy metabolism in the Drosophila mushroom body is the trigger for long-term memory

     Nature Communications 8:15510.

     https://doi.org/10.1038/ncomms15510

     • PubMed
     • Google Scholar
117. 1. Qin H
     2. Cressy M
     3. Li W
     4. Coravos JS
     5. Izzi SA
     6. Dubnau J

     (2012) Gamma neurons mediate dopaminergic input during aversive olfactory memory formation in Drosophila

     Current Biology 22:608–614.

     https://doi.org/10.1016/j.cub.2012.02.014

     • PubMed
     • Google Scholar
118. 1. Rasmussen HH
     2. Mortensen PB
     3. Jensen IW

     (1990) Depression and magnesium deficiency

     The International Journal of Psychiatry in Medicine 19:57–63.

     https://doi.org/10.2190/NKCD-1RB1-QMA9-G1VN

     • Google Scholar
119. 1. Romani A
     2. Scarpa A

     (1990a) Norepinephrine evokes a marked Mg²⁺ efflux from liver cells

     FEBS Letters 269:37–40.

     https://doi.org/10.1016/0014-5793(90)81113-3

     • PubMed
     • Google Scholar
120. 1. Romani A
     2. Scarpa A

     (1990b) Hormonal control of Mg2+ transport in the heart

     Nature 346:841–844.

     https://doi.org/10.1038/346841a0

     • PubMed
     • Google Scholar
121. 1. Romani AM
     2. Scarpa A

     (2000) Regulation of cellular magnesium

     Frontiers in Bioscience 5:d720–d734.

     https://doi.org/10.2741/Romani

     • PubMed
     • Google Scholar
122. 1. Rosay P
     2. Armstrong JD
     3. Wang Z
     4. Kaiser K

     (2001) Synchronized neural activity in the Drosophila memory centers and its modulation by amnesiac

     Neuron 30:759–770.

     https://doi.org/10.1016/S0896-6273(01)00323-3

     • PubMed
     • Google Scholar
123. 1. Sartori SB
     2. Whittle N
     3. Hetzenauer A
     4. Singewald N

     (2012) Magnesium deficiency induces anxiety and HPA axis dysregulation: modulation by therapeutic drug treatment

     Neuropharmacology 62:304–312.

     https://doi.org/10.1016/j.neuropharm.2011.07.027

     • PubMed
     • Google Scholar
124. 1. Schindelin J
     2. Arganda-Carreras I
     3. Frise E
     4. Kaynig V
     5. Longair M
     6. Pietzsch T
     7. Preibisch S
     8. Rueden C
     9. Saalfeld S
     10. Schmid B
     11. Tinevez JY
     12. White DJ
     13. Hartenstein V
     14. Eliceiri K
     15. Tomancak P
     16. Cardona A

     (2012) Fiji: an open-source platform for biological-image analysis

     Nature Methods 9:676–682.

     https://doi.org/10.1038/nmeth.2019

     • PubMed
     • Google Scholar
125. 1. Schwaerzel M
     2. Monastirioti M
     3. Scholz H
     4. Friggi-Grelin F
     5. Birman S
     6. Heisenberg M

     (2003) Dopamine and octopamine differentiate between aversive and appetitive olfactory memories in Drosophila

     The Journal of Neuroscience 23:10495–10502.

     https://doi.org/10.1523/JNEUROSCI.23-33-10495.2003

     • PubMed
     • Google Scholar
126. 1. Shindo Y
     2. Yamanaka R
     3. Suzuki K
     4. Hotta K
     5. Oka K

     (2016) Altered expression of Mg 2+ transport proteins during Parkinson's disease-like dopaminergic cell degeneration in PC12 cells

     Biochimica et Biophysica Acta (BBA) - Molecular Cell Research 1863:1979–1984.

     https://doi.org/10.1016/j.bbamcr.2016.05.003

     • Google Scholar
127. 1. Slutsky I
     2. Sadeghpour S
     3. Li B
     4. Liu G

     (2004) Enhancement of synaptic plasticity through chronically reduced Ca²⁺ flux during uncorrelated activity

     Neuron 44:835–849.

     https://doi.org/10.1016/j.neuron.2004.11.013

     • PubMed
     • Google Scholar
128. 1. Slutsky I
     2. Abumaria N
     3. Wu LJ
     4. Huang C
     5. Zhang L
     6. Li B
     7. Zhao X
     8. Govindarajan A
     9. Zhao MG
     10. Zhuo M
     11. Tonegawa S
     12. Liu G

     (2010) Enhancement of learning and memory by elevating brain magnesium

     Neuron 65:165–177.

     https://doi.org/10.1016/j.neuron.2009.12.026

     • PubMed
     • Google Scholar
129. 1. Tanaka NK
     2. Awasaki T
     3. Shimada T
     4. Ito K

     (2004) Integration of chemosensory pathways in the Drosophila second-order olfactory centers

     Current Biology 14:449–457.

     https://doi.org/10.1016/j.cub.2004.03.006

     • PubMed
     • Google Scholar
130. 1. Tanaka NK
     2. Tanimoto H
     3. Ito K

     (2008) Neuronal assemblies of the Drosophila mushroom body

     The Journal of Comparative Neurology 508:711–755.

     https://doi.org/10.1002/cne.21692

     • PubMed
     • Google Scholar
131. 1. Tang YP
     2. Shimizu E
     3. Dube GR
     4. Rampon C
     5. Kerchner GA
     6. Zhuo M
     7. Liu G
     8. Tsien JZ

     (1999) Genetic enhancement of learning and memory in mice

     Nature 401:63–69.

     https://doi.org/10.1038/43432

     • PubMed
     • Google Scholar
132. 1. Tomchik SM
     2. Davis RL

     (2009) Dynamics of learning-related cAMP signaling and stimulus integration in the Drosophila olfactory pathway

     Neuron 64:510–521.

     https://doi.org/10.1016/j.neuron.2009.09.029

     • PubMed
     • Google Scholar
133. 1. Tully T
     2. Preat T
     3. Boynton SC
     4. Del Vecchio M

     (1994) Genetic dissection of consolidated memory in Drosophila

     Cell 79:35–47.

     https://doi.org/10.1016/0092-8674(94)90398-0

     • PubMed
     • Google Scholar
134. 1. Tully T
     2. Quinn WG

     (1985) Classical conditioning and retention in normal and mutant Drosophila melanogaster

     Journal of Comparative Physiology A 157:263–277.

     https://doi.org/10.1007/BF01350033

     • Google Scholar
135. 1. Turrigiano GG

     (2008) The self-tuning neuron: synaptic scaling of excitatory synapses

     Cell 135:422–435.

     https://doi.org/10.1016/j.cell.2008.10.008

     • PubMed
     • Google Scholar
136. 1. Venken KJ
     2. Schulze KL
     3. Haelterman NA
     4. Pan H
     5. He Y
     6. Evans-Holm M
     7. Carlson JW
     8. Levis RW
     9. Spradling AC
     10. Hoskins RA
     11. Bellen HJ

     (2011) MiMIC: a highly versatile transposon insertion resource for engineering Drosophila melanogaster genes

     Nature Methods 8:737–743.

     https://doi.org/10.1038/nmeth.1662

     • PubMed
     • Google Scholar
137. Book

     1. Vink R
     2. Nechifor M

     (2011)

     Magnesium in the Central Nervous System

     University of Adelaide Press.

     • Google Scholar
138. 1. Vormann J
     2. Günther T

     (1987)

     Amiloride-sensitive net Mg²⁺ efflux from isolated perfused rat hearts

     Magnesium 6:220–224.

     • PubMed
     • Google Scholar
139. 1. Vural H
     2. Demirin H
     3. Kara Y
     4. Eren I
     5. Delibas N

     (2010) Alterations of plasma magnesium, copper, zinc, iron and selenium concentrations and some related erythrocyte antioxidant enzyme activities in patients with Alzheimer's disease

     Journal of Trace Elements in Medicine and Biology 24:169–173.

     https://doi.org/10.1016/j.jtemb.2010.02.002

     • PubMed
     • Google Scholar
140. 1. Whittle N
     2. Li L
     3. Chen WQ
     4. Yang JW
     5. Sartori SB
     6. Lubec G
     7. Singewald N

     (2011) Changes in brain protein expression are linked to magnesium restriction-induced depression-like behavior

     Amino Acids 40:1231–1248.

     https://doi.org/10.1007/s00726-010-0758-1

     • PubMed
     • Google Scholar
141. 1. Wu CL
     2. Xia S
     3. Fu TF
     4. Wang H
     5. Chen YH
     6. Leong D
     7. Chiang AS
     8. Tully T

     (2007) Specific requirement of NMDA receptors for long-term memory consolidation in Drosophila ellipsoid body

     Nature Neuroscience 10:1578–1586.

     https://doi.org/10.1038/nn2005

     • PubMed
     • Google Scholar
142. 1. Wu JS
     2. Luo L

     (2006) A protocol for dissecting Drosophila melanogaster brains for live imaging or immunostaining

     Nature Protocols 1:2110–2115.

     https://doi.org/10.1038/nprot.2006.336

     • PubMed
     • Google Scholar
143. 1. Xia S
     2. Miyashita T
     3. Fu TF
     4. Lin WY
     5. Wu CL
     6. Pyzocha L
     7. Lin IR
     8. Saitoe M
     9. Tully T
     10. Chiang AS

     (2005) NMDA receptors mediate olfactory learning and memory in Drosophila

     Current Biology 15:603–615.

     https://doi.org/10.1016/j.cub.2005.02.059

     • PubMed
     • Google Scholar
144. 1. Yamazaki D
     2. Funato Y
     3. Miura J
     4. Sato S
     5. Toyosawa S
     6. Furutani K
     7. Kurachi Y
     8. Omori Y
     9. Furukawa T
     10. Tsuda T
     11. Kuwabata S
     12. Mizukami S
     13. Kikuchi K
     14. Miki H

     (2013) Basolateral Mg2+ extrusion via CNNM4 mediates transcellular Mg2+ transport across epithelia: a mouse model

     PLOS Genetics 9:e1003983.

     https://doi.org/10.1371/journal.pgen.1003983

     • PubMed
     • Google Scholar
145. 1. Yang MY
     2. Armstrong JD
     3. Vilinsky I
     4. Strausfeld NJ
     5. Kaiser K

     (1995) Subdivision of the Drosophila mushroom bodies by enhancer-trap expression patterns

     Neuron 15:45–54.

     https://doi.org/10.1016/0896-6273(95)90063-2

     • PubMed
     • Google Scholar
146. 1. Yasuyama K
     2. Meinertzhagen IA
     3. Schürmann FW

     (2002) Synaptic organization of the mushroom body calyx in Drosophila melanogaster

     Journal of Comparative Neurology 445:211–226.

     https://doi.org/10.1002/cne.10155

     • PubMed
     • Google Scholar
147. 1. Yoon YK
     2. Kim JH
     3. Kim JH
     4. Kwon JY
     5. Kim YC
     6. Kim YJ
     7. Park ZY

     (2016) Pyrazolodiazepine derivatives with agonist activity toward Drosophila RYamide receptor

     Bioorganic & Medicinal Chemistry Letters 26:5116–5118.

     https://doi.org/10.1016/j.bmcl.2016.08.039

     • PubMed
     • Google Scholar
148. 1. Yu D
     2. Akalal DB
     3. Davis RL

     (2006) Drosophila alpha/beta mushroom body neurons form a branch-specific, long-term cellular memory trace after spaced olfactory conditioning

     Neuron 52:845–855.

     https://doi.org/10.1016/j.neuron.2006.10.030

     • PubMed
     • Google Scholar
149. 1. Yu Z
     2. Ren M
     3. Wang Z
     4. Zhang B
     5. Rong YS
     6. Jiao R
     7. Gao G

     (2013) Highly efficient genome modifications mediated by CRISPR/Cas9 in Drosophila

     Genetics 195:289–291.

     https://doi.org/10.1534/genetics.113.153825

     • PubMed
     • Google Scholar
150. 1. Zagotta WN
     2. Olivier NB
     3. Black KD
     4. Young EC
     5. Olson R
     6. Gouaux E

     (2003) Structural basis for modulation and agonist specificity of HCN pacemaker channels

     Nature 425:200–205.

     https://doi.org/10.1038/nature01922

     • PubMed
     • Google Scholar
151. 1. Zars T
     2. Fischer M
     3. Schulz R
     4. Heisenberg M

     (2000) Localization of a short-term memory in Drosophila

     Science 288:672–675.

     https://doi.org/10.1126/science.288.5466.672

     • PubMed
     • Google Scholar
152. 1. Zhang H
     2. Kozlov G
     3. Li X
     4. Wu H
     5. Gulerez I
     6. Gehring K

     (2017) PRL3 phosphatase active site is required for binding the putative magnesium transporter CNNM3

     Scientific Reports 7:48.

     https://doi.org/10.1038/s41598-017-00147-2

     • PubMed
     • Google Scholar
153. 1. Zhang Y
     2. Skolnick J

     (2005) TM-align: a protein structure alignment algorithm based on the TM-score

     Nucleic Acids Research 33:2302–2309.

     https://doi.org/10.1093/nar/gki524

     • PubMed
     • Google Scholar
154. 1. Zimmer CT
     2. Garrood WT
     3. Puinean AM
     4. Eckel-Zimmer M
     5. Williamson MS
     6. Davies TG
     7. Bass C

     (2016) A CRISPR/Cas9 mediated point mutation in the alpha 6 subunit of the nicotinic acetylcholine receptor confers resistance to spinosad in Drosophila melanogaster

     Insect Biochemistry and Molecular Biology 73:62–69.

     https://doi.org/10.1016/j.ibmb.2016.04.007

     • PubMed
     • Google Scholar

Acceptance summary:

Wu et al. discover elevated dietary magnesium enhances long-term memory in Drosophila. They then identify target neurons (α/β Kenyon Cells of the mushroom body) and a protein critical for the effect, the CNNM2 ortholog Unextended (UEX), which the authors implicate in magnesium efflux. The study is well-performed and conclusions justified by the data presented. Overall, this paper marks an important step in examining a highly significant, but understudied topic.

Decision letter after peer review:

Thank you for submitting your article "Magnesium efflux from Drosophila Kenyon Cells is critical for normal and diet-enhanced long-term memory" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by K VijayRaghavan as the Senior Editor and Reviewing Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.

Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in eLife, either of which would be linked to the original paper.

Summary:

Supplemental dietary magnesium enhances learning and memory in rats, an observation with implications for humans. The underlying mechanisms are not known, although it is correlated with increased hippocampal synaptic transmission and plasticity. Here Wu et al. discover elevated dietary magnesium also enhances long term memory in Drosophila. They then identify target neurons (α/β Kenyon Cells of the mushroom body) and a protein critical for the effect, the CNNM2 ortholog Unextended (UEX), which the authors implicate in magnesium efflux. The study is well-performed and conclusions justified by the data presented. Overall, this paper marks an important step in examining a highly significant, but understudied topic. How dietary magnesium influences memory is at least in part, is ascribed to changes in synaptic density via elevated NMDA receptor expression. However, this connection cannot explain all facets and, given the importance of memory-enhancing treatments for sufferers of neurodegenerative disease, it is an important question. The authors discover that elevated dietary magnesium enhances long term memory performance in Drosophila. They identify a likely set of target neurons (α/β Kenyon Cells) and a protein critical for this effect, a multi-pass transmembrane protein, the Drosophila CNNM2 ortholog Unextended (UEX). The authors demonstrate that UEX acts in the α/β KCs of the mushroom body to support both appetitive and aversive long term (24h) memory performance, and provide evidence that UEX promotes magnesium efflux. UEX functions in the αβ Kenyon Cells in the mushroom body and requires its cyclic nucleotide binding domain for proper function. Consistently, in spirit, alterations of cAMP levels using classical memory mutants alter localization of UEX. Finally, the authors identify a slow oscillation of magnesium in Kenyon Cells that requires UEX function.

At a technical level, the behavioural and molecular genetic aspects of the study (including the tagging of the endogenous protein and the creation of site-specific genomic mutants) are very well done. These experiments are thorough and well-executed, with appropriate controls, and the conclusions drawn justified by the data presented.

There are many issues raised by the study that provide fertile topics for future work, from details such as how cyclic nucleotide binding affects UEX trafficking to bigger picture issues including the mechanism by which UEX-mediated magnesium efflux contributes to memory and the dietary effects of magnesium on memory, not to mention what are the key targets of magnesium and how magnesium oscillations contribute to memory. However, while those are worthy topics for future studies, the paper as it stands constitutes a significant advance worthy of publication in eLife.

However, there are several concerns that need to be addressed before acceptance. We would prefer that they be addressed experimentally, where indicated, and done so speedily. We understand that the absence of reagents, time and access could make this a difficult or impossible requirement to meet. In that case, the manuscript should insert appropriate caveats in interpretation.

Revisions for this paper:

1) The increase in α/β lobe MagFRET-1 FRET signal in Figure 1E is modestly enhanced by 80 mM dietary MgCl₂ (under 10%). Given the apparent affinity of the sensor for Mg²⁺ (Km ~ 150 microM ) and the ~50% increase in FRET signal upon Mg²⁺ binding, do the authors have a sense of what such an increase would correspond to in terms of actual Mg²⁺ concentration?

2) On a related point, the MagFRET-1 experiment was done on formaldehyde fixed tissue. Is it clear that the sensor provides an accurate reflection of in vivo magnesium levels after fixation and washing?

3) Uex mutations affect both aversive and appetitive memory. Is the same true for Mg²⁺ supplementation?

4) How do the authors rationalize the role of a magnesium efflux transporter (UEX) in supporting the effect of elevated dietary magnesium? Naively, one would anticipate that UEX would act to counter the effects of higher levels of magnesium.

5) In a few places, the jargon and common practice of Drosophila genetics is not well enough explained for a non-fly audience. For example, the discussion of Nmdar RNAi (subsection “Mg²⁺ enhanced memory is independent of NMDAR in the mushroom bodies”) and the use of GAL80-TS (subsection “A role for uex in the mushroom bodies”) should be more generally described to understand the experimental logic.

6) The authors indicate that αβc knockdown causes a phenotype (Figure 3C) but UAS expression in those cells does not rescue the phenotype (Figure 4A). Do the authors have an explanation for the discrepancy?

Revisions potentially involving experimental additions:

7) In Figure 5, the human relative CNNM2 is used to rescue the uex mutant fly. Mutant CNNM2 variants associated with disease in humans are reported to not rescue the fly, but it is not clear whether the failure to rescue is caused by altered protein function or a failure of protein expression/localization. Expression and localization of the CNNM2 mutant proteins should be examined. If that is not possible, the authors should note these as possible explanations for the failure to rescue.

Also, what do these point mutants do? Can the authors do cell assays to verify that magnesium efflux is blocked in these mutants (as in Figure 5—figure supplement 2)? Or alternatively indicate references and data where appropriate

8) The impact of the T626NRR mutation on protein function is unclear, raising the concern that it could have a broader impact on the protein than simply altering nucleotide binding domain function. Is the mutant protein expressed and localized properly? Does the mutant protein have altered cAMP binding? Does it affect magnesium efflux activity? Barring massive experiments, a repeat of their MagIC experiment from Figure 8 using that specific construct would be satisfactory. If the authors do not know what the biochemical impact of this lesion is and are unable to carry out this experiment at present, they should insert appropriate caveats when interpreting the phenotype of this mutant.

9) Why were the HEK cell experiments done with a human CNNM4 while the fly experiments were done with human CNNM2? They're homologous, but why not use the same protein in each experiment to strengthen the parallels.

Revisions for this paper:

1) The increase in α/β lobe MagFRET-1 FRET signal in Figure 1E is modestly enhanced by 80 mM dietary MgCl₂ (under 10%). Given the apparent affinity of the sensor for Mg²⁺ (Km ~ 150 microM ) and the ~50% increase in FRET signal upon Mg²⁺ binding, do the authors have a sense of what such an increase would correspond to in terms of actual Mg²⁺ concentration?

As suggested by the reviewer, we have now used the MagFRET-1 signal enhancement observed in the α/β lobes to estimate the change in Mg²⁺ concentration that results from 80mM dietary MgCl₂.

If full occupancy of the reporter gives a 50% increase in FRET and the Kd (concentration that produces half occupancy) = 148uM then a 50% increase in FRET corresponds to a real change in [Mg²⁺] of 296µM.

In Figure 1E, for the α lobe the mean change in the emission ratio as a percentage is = (0.8340-0.7919)/ 0.7919 = 5.32% which corresponds to Δ[Mg²⁺] of 31.49 µM. For the β Lobe, the mean change in emission ratio as a percentage is = (0.7356-0.6650)/ 0.6650 = 10.60%, corresponding to Δ[Mg²⁺] of 62.75 µM. Averaging across the α and β lobes therefore gives us a Δ[Mg²⁺] 47.12 µM. We therefore conclude that feeding the flies 80mM of dietary MgCl₂ produces an ~50 µM increase of KC [Mg²⁺]_i on average.

The following sentence has been added:

“Given the affinity of MagFRET-1 (Kd = 148 µM) and the ~50% increase in FRET signal upon Mg²⁺ binding (Lindenburg et al., 2013), we estimate that the ~8% enhancement of the MagFRET signal measured in flies fed 80mN MgCl₂ corresponds to an ~50 µM increase of αβ KC [Mg²⁺]i on average.”

2) On a related point, the MagFRET-1 experiment was done on formaldehyde fixed tissue. Is it clear that the sensor provides an accurate reflection of in vivo magnesium levels after fixation and washing?

We do not know how fixation and washing might change the property of the sensor. However, we think it’s reasonable to assume that any change that occurs from fixation and/or washing change would happen in a consistent way in the brains from normal flies and those fed with high dietary Mg²⁺. Therefore, the difference in [Mg²⁺]_i observed between the conditions is presumably retained after the fixation and washing process, that is equally applied to all flies.

We did also try to use MagFRET and MagIC to compare the [Mg²⁺]_i in normal and high Mg²⁺ diet flies using an in vivo measurement. However, the variation in these in vivo experiments appears to be too high to draw any convincing conclusions. We provide the MagIC data in Author response image 1 for the reviewers but do not include it in the manuscript:

Author response image 1

Download asset Open asset

Following these in vivo experiments with MagFRET and MagIC we consider it possible that the fixation procedure applied to MagFRET may actually help to capture the current brain state and thereby enable a quantitative comparison between conditions. Perhaps this is especially important when the change in concentration is as subtle as ~50 µM.

3) Uex mutations affect both aversive and appetitive memory. Is the same true for Mg++ supplementation?

Yes, the same is also true for Mg²⁺ supplementation. These new data have been added to the manuscript as Figure 4—figure supplement 1. The corresponding citations in the manuscript have been updated.

The following text has been added:

“We also tested whether 4 days of 80mM MgCl₂ supplementation enhanced 24 hr memory performance following aversive spaced training. Again, memory of wild-type, but not uex^MI01943 mutant flies showed enhancement (Figure 4—figure supplement 1).”

4) How do the authors rationalize the role of a magnesium efflux transporter (UEX) in supporting the effect of elevated dietary magnesium? Naively, one would anticipate that UEX would act to counter the effects of higher levels of magnesium.

We can only provide a hypothetical suggestion at the moment and we have added the following statement in the Discussion:

“It perhaps seems counterintuitive that UEX-directed magnesium efflux is required in KCs to support the memory-enhancing effects of Mg²⁺ feeding, when dietary Mg²⁺ elevates KC [Mg²⁺]_i. […] Our live-imaging of KC [Mg²⁺]_i in wild-type and uex mutant brains suggests that UEX-directed efflux is likely to be an essential factor in the active, and perhaps stimulus evoked, homeostatic maintenance of these elevated levels.”

5) In a few places, the jargon and common practice of Drosophila genetics is not well enough explained for a non-fly audience. For example, the discussion of Nmdar RNAi (subsection “Mg²⁺ enhanced memory is independent of NMDAR in the mushroom bodies”) and the use of GAL80-TS (subsection “A role for uex in the mushroom bodies”) should be more generally described to understand the experimental logic.

On re-reading the manuscript we now see the overly heavy jargon and extent of assumptions of knowledge. We have amended the section to more clearly describe the reagents used for RNA interference (RNAi) targeting the NMDAR genes in the fly. We have also improved the section in the text related to the logic and use of GAL80-TS.

“We next directly tested whether Mg²⁺ enhanced memory required NMDAR function, by knocking down expression of the Nmdar1 or Nmdar2 genes using transgenic UAS-driven RNA interference (RNAi) constructs. […] In contrast, more selective expression of this UAS-Nmdar1^RNAi in long-term memory (LTM) relevant αβ KCs using c739-GAL4 did not significantly impair 24 hr memory performance (Figure 1—figure supplement 1B).”

“To reduce the likelihood that the uex^RNAi associated memory defect results from a developmental consequence, we also restricted UAS-uex^RNAi expression to adulthood using GAL80^ts-mediated temporal control (McGuire et al., 2003). […] Restricting UAS-uex^RNAi expression to αβ KCs in adult flies using c739-GAL4 with GAL80^ts produced a similar 24 hr specific memory defect to that observed when UAS-uex^RNAi was expressed without temporal control (Figure 3D-F).”

6) The authors indicate that αβc knockdown causes a phenotype (Figure 3C) but UAS expression in those cells does not rescue the phenotype (Figure 4A). Do the authors have an explanation for the discrepancy?

To clarify the interpretation of results, we added the following:

“Finding that αβ_c RNAi knockdown of uex produces a memory defect (Figure 3C) but UAS-uex expression in αβ_c does not rescue the uex^MI01943 mutant defect (Figure 4A) suggests that UEX function in αβ_c KCs is essential for appetitive LTM, whereas both the αβ_c and αβ_s KCs need to have functional UEX to support LTM. “

Revisions potentially involving experimental additions:

7) In Figure 5, the human relative CNNM2 is used to rescue the uex mutant fly. Mutant CNNM2 variants associated with disease in humans are reported to not rescue the fly, but it is not clear whether the failure to rescue is caused by altered protein function or a failure of protein expression/localization. Expression and localization of the CNNM2 mutant proteins should be examined. If that is not possible, the authors should note these as possible explanations for the failure to rescue.

Also, what do these point mutants do? Can the authors do cell assays to verify that magnesium efflux is blocked in these mutants (as in Figure 5—figure supplement 2)? Or alternatively indicate references and data where appropriate.

We have now confirmed the expression of the CNNM2 variants in the fly brain by immuno-staining using the C-terminal HA tag that is added to all of the CNNM2 variant cDNA clones. These data show that every variant is expressed at comparable levels when driven by c739-GAL4. These data have been added as a new Figure 5—figure supplement 1.

Regarding the effect of these CNNM2 mutant variants on magnesium transporting, experiments were carried out in the original paper (Arjona et al., 2014) (Figure 3A). We have added the following text:

“Several point mutations in CNNM2 have been identified in human patients with hypomagnesemia, which is associated with brain malformation and intellectual disability (Arjona et al., 2014). […] Staining for an associated C-terminal HA-tag revealed clear expression of all UAS-CNNM2::HA variants in αβ neurons when driven with c739-GAL4 (Figure 5—figure supplement 1).”

8) The impact of the T626NRR mutation on protein function is unclear, raising the concern that it could have a broader impact on the protein than simply altering nucleotide binding domain function. Is the mutant protein expressed and localized properly? Does the mutant protein have altered cAMP binding? Does it affect magnesium efflux activity? Barring massive experiments, a repeat of their MagIC experiment from Figure 8 using that specific construct would be satisfactory. If the authors do not know what the biochemical impact of this lesion is and are unable to carry out this experiment at present, they should insert appropriate caveats when interpreting the phenotype of this mutant.

These are important issues that we have now addressed in the manuscript. We have checked the expression of the T626NRR mutant protein via western blot and have added the data as panel E of Figure 6. The proteins all appear to be expressed at comparable levels in the KCs. The figure legend is updated accordingly. We also attempted MagIC experiments using the T626NRR mutant but have so far failed to generate flies carrying all the transgenes in the T626NRR mutant background. Text describing these data and stating caveats is now added:

“Although we confirmed using western blotting that a full-length protein is expressed in uex^T622NRR flies (Figure 6E), our antibody did not permit us to verify that the UEX^T626NRR protein localizes appropriately in the brain. Further work is therefore required to characterize the cellular localization, cAMP binding and Mg²⁺ transport function of the protein encoded by this serendipitous uex^T626NRR allele.”

Also, a subsection “Anti-UEX antibody and Western blot” has been added in the Materials and methods section of the manuscript.

9) Why were the HEK cell experiments done with a human CNNM4 while the fly experiments were done with human CNNM2? They're homologous, but why not use the same protein in each experiment to strengthen the parallels.

We emphasized conservation between UEX in the fly and mammalian CNNM2/4. In the HEK293 cell experiments, the human CNNM4 construct was only used as a positive control, and there was no intention to compare the extent of Mg²⁺ extrusion activity of CNNM4 and UEX in detail because we are currently unsure if their expression is comparable in HEK cells. Moreover, similar extrusion activity of CNNM2 and CNNM4 was previously established in Figure 1 of Hirata et al., 2014. We have added the following sentence:

“Mg²⁺ extrusion driven by UEX was noticeably less efficient than in cells expressing Human CNNM4 (Figure 5—figure supplement 2B), which is known to have similar efficiency to CNNM2 (Hirata et al., 2014). […] Nevertheless, demonstration of cross-species complementation and Mg²⁺ efflux activity defines UEX as a functional homolog of mammalian CNNM2/4.”

Author details

1. Yanying Wu

   Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Oxford, United Kingdom

   Contribution

   Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

2. Yosuke Funato

   Department of Cellular Regulation, Research Institute for Microbial Diseases, Osaka University, Suita, Japan

   Contribution

   Formal analysis, Validation, Investigation, Visualization, Methodology

   Competing interests

   No competing interests declared

3. Eleonora Meschi

   Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Oxford, United Kingdom

   Contribution

   Formal analysis, Investigation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2401-7969

4. Kristijan D Jovanoski

   Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Oxford, United Kingdom

   Contribution

   Formal analysis, Investigation, Methodology

   Competing interests

   No competing interests declared

5. Hiroaki Miki

   Department of Cellular Regulation, Research Institute for Microbial Diseases, Osaka University, Suita, Japan

   Contribution

   Resources, Supervision, Funding acquisition, Methodology

   Competing interests

   No competing interests declared

6. Scott Waddell

   Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Oxford, United Kingdom

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   scott.waddell@cncb.ox.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4503-6229

• 3,319

  Page views

• 425

  Downloads

• 5

  Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.