Zinc and copper are involved in neuronal differentiation and synaptic plasticity but the molecular mechanisms behind these processes are still elusive due in part to the difficulty of imaging trace metals together with proteins at the synaptic level. We correlate stimulated emission depletion microscopy of proteins and synchrotron X-ray fluorescence imaging of trace metals, both performed with 40 nm spatial resolution, on primary rat hippocampal neurons. We reveal the co-localization at the nanoscale of zinc and tubulin in dendrites with a molecular ratio of about one zinc atom per tubulin-αβ dimer. We observe the co-segregation of copper and F-actin within the nano-architecture of dendritic protrusions. In addition, zinc chelation causes a decrease in the expression of cytoskeleton proteins in dendrites and spines. Overall, these results indicate new functions for zinc and copper in the modulation of the cytoskeleton morphology in dendrites, a mechanism associated to neuronal plasticity and memory formation.
Synchrotron datasets (SXRF and PCI images) are available from the ESRF data portal in open mode with the following DOI numbers: doi:10.15151/ESRF-ES-162248067 (https://doi.esrf.fr/10.15151/ESRF-ES-162248067) and doi:10.15151/ESRF-ES-101127303 (https://doi.esrf.fr/10.15151/ESRF-ES-101127303). Figure 1-source data 1. Data are available at https://doi.esrf.fr/10.15151/ESRF-ES-162248067 datasets M20_zone67_nfp3_015nm and M20_zone67_fine01. Table 1-source data 1. Table1 Source data 1.xlsx. Figure 2-source data 1. Data are available at https://doi.esrf.fr/10.15151/ESRF-ES-101127303 datasets TA15_neu64_fine2 and TA15_neu64_fine5. Figure 3-source data 1. Data are available at https://doi.esrf.fr/10.15151/ESRF-ES-162248067 datasets M8_neur43_sted44_nfp_015nm and M8_neu43_fine03. Figure 4-source data 1. Data are available at https://doi.esrf.fr/10.15151/ESRF-ES-101127303 dataset TA15_neu71_fine01. Figure 4-source data 2. Data for Pearson's correlation coefficients are included in Figure 4 source data 2.zip Figure 5-source data 1. Data are available at https://doi.esrf.fr/10.15151/ESRF-ES-101127303 datasets TA15- neu 26 fine 01 and TA15_neu23_fine02. Figure 6-source data 1. Data for F-actin are available in file Figure 6 source data 1.xlxs. Figure 6-source data 2. Data for β-tubulin are available in file Figure 6 source data 2.xlxs. Figure 2-source data 2. Synchrotron XRF data for Figure 2-figure supplement 1 are available at https://doi.esrf.fr/10.15151/ESRF-ES-101127303 datasets TA15_neu64_fine4 and TA15_neu64_fine3. Figure 2-source data 3. Data for Pearson's correlation coefficients of Figure 2-figure supplement 1 panel h are provided in Figure 2 source data 3.zip Figure 2-source data 4. Data for Pearson's correlation coefficients of of Figure 2-figure supplement 1 panel o are provided in Figure 2 source data 4.zip Figure3-source data 2. Synchrotron XRF data for Figure 3-figure supplement 1 are available at https://doi.esrf.fr/10.15151/ESRF-ES-101127303 dataset SiTA1_neu7_fine01. Figure 4-figure source data 2. Synchrotron XRF and PCI data for Figure 4-figure supplement 1 are available at https://doi.esrf.fr/10.15151/ESRF-ES-162248067 datasets M20_zone67_fine01, M20_zone67_fine02, and M20_zone67_fine06. Figure 5-source data 2. Synchrotron XRF data for Figure 5-figure supplement 1 are available at https://doi.esrf.fr/10.15151/ESRF-ES-162248067 datasets M20_zone67_nfp3_015nm and M20_zone67_fine01. Figure 6-source data 3. F-actin data for Figure 6-figure supplement 1 are available in file Figure 6 source data 3.xlxs. Figure 6-source data 4. Tubulin data for Figure 6-figure supplement 1 are available in file Figure6 source data 4.xlxs. Supplementary File 1. Raw data provided in Source Data 1, file Source data 1.xlsx.
Correlative X-ray microscopy and super-resolution microscopy of freeze dried hippocampal neurons. European Synchrotron Radiation Facility (ESRF)ESRF data portal, ESRF-ES-101127303.
- Richard Ortega
- Daniel Choquet
- Richard Ortega
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- John Kuriyan, University of California, Berkeley, United States
© 2020, Domart et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Acid-sensing ion channels (ASICs) are trimeric proton-gated sodium channels. Recent work has shown that these channels play a role in necroptosis following prolonged acidic exposure like occurs in stroke. The C-terminus of ASIC1a is thought to mediate necroptotic cell death through interaction with receptor interacting serine threonine kinase 1 (RIPK1). This interaction is hypothesized to be inhibited at rest via an interaction between the C- and N-termini which blocks the RIPK1 binding site. Here, we use two transition metal ion FRET methods to investigate the conformational dynamics of the termini at neutral and acidic pH. We do not find evidence that the termini are close enough to be bound while the channel is at rest and find that the termini may modestly move closer together during acidification. At rest, the N-terminus adopts a conformation parallel to the membrane about 10 Å away. The distal end of the C-terminus may also spend time close to the membrane at rest. After acidification, the proximal portion of the N-terminus moves marginally closer to the membrane whereas the distal portion of the C-terminus swings away from the membrane. Together these data suggest that a new hypothesis for RIPK1 binding during stroke is needed.
Decisions under uncertainty are often biased by the history of preceding sensory input, behavioral choices, or received outcomes. Behavioral studies of perceptual decisions suggest that such history-dependent biases affect the accumulation of evidence and can be adapted to the correlation structure of the sensory environment. Here, we systematically varied this correlation structure while human participants performed a canonical perceptual choice task. We tracked the trial-by-trial variations of history biases via behavioral modeling and of a neural signature of decision formation via magnetoencephalography (MEG). The history bias was flexibly adapted to the environment and exerted a selective effect on the build-up (not baseline level) of action-selective motor cortical activity during decision formation. This effect added to the impact of the current stimulus. We conclude that the build-up of action plans in human motor cortical circuits is shaped by dynamic prior expectations that result from an adaptive interaction with the environment.