Protein kinase C modulates the activity of a cloned gamma-aminobutyric acid transporter expressed in Xenopus oocytes via regulated subcellular redistribution of the transporter

We report that activators and inhibitors of protein kinase C (PKC) and protein phosphatases regulate the activity of a cloned rat brain gamma- aminobutyric acid (GABA) transporter (GAT1) expressed in Xenopus oocytes. Four compounds known to activate PKC increased GABA uptake 2- 3.5-fold over basal control levels. Inhibition of PKC by bisindolylmaleimide reduced basal GABA uptake 80% and blocked the phorbol 12-myristate 13-acetate (PMA)-induced stimulation of transport. Okadaic acid, a protein phosphatase inhibitor, stimulated transport 2.5- fold; a 4-fold increase in GABA uptake occurred when oocytes were treated with cyclosporin A, a specific inhibitor of protein phosphatase 2B. Modulation resulted in changes to Vmax but not to Km and was influenced by the functional expression level of the transporter protein; as expression level increased, the ability to up-regulate transporter activity decreased. Down-regulation of transporter activity was independent of expression level. Modulation did not occur through phosphorylation of the three consensus PKC sites predicted by the primary protein sequence since their removal had no effect on the susceptibility of the transporter to modulation by PMA or bisindolylmaleimide. Subcellular fractionation of oocyte membranes demonstrated that under basal level conditions, the majority of GAT1 was targeted to a cytoplasmic compartment corresponding to the trans- Golgi or low density vesicles. Stimulation of PKC with PMA resulted in a translocation of transporters from this compartment to the plasma membrane. At higher expression levels of GAT1 protein, a larger portion of GAT1 was found on the plasma membrane during basal level conditions and treatment with bisindolylmaleimide resulted in removal of these transporters from the plasma membrane. At expression levels demonstrated to be resistant to modulation by PMA, PMA-treatment still resulted in translocation of transporters from the cytoplasm to the plasma membrane. Thus, the inability of PMA to increase uptake at high expression of the GAT1 protein is due to saturation at a step subsequent to translocation. These findings 1) demonstrate the presence of a novel regulated secretory pathway in oocytes and 2) suggest a modulatory mechanism for neurotransmitter transporters that could have significant effects upon synaptic function

Second Messengers, Trafficking-Related Proteins, and Amino Acid Residues that Contribute to the Functional Regulation of the Rat Brain GABA Transporter GAT1

Recent evidence indicates that several members of the Na⁺-coupled transporter family are regulated, and this regulation in part occurs by redistribution of transporters between intracellular locations and the plasma membrane. We elucidate components of this process for both wild-type and mutant GABA transporters (GAT1) expressed in Xenopus oocytes using a combination of uptake assays, immunoblots, and electrophysiological measurements of membrane capacitance, transport-associated currents, and GAT1-specific charge movements. At low GAT1 expression levels, activators of protein kinase C (PKC) induce redistribution of GAT1 from intracellular vesicles to the plasma membrane; at higher GAT1 expression levels, activators of PKC fail to induce this redistribution. However, coinjection of total rat brain mRNA with GAT1 permits PKC-mediated modulation at high transporter expression levels. This effect of brain mRNA on modulation is mimicked by coinjection of syntaxin 1a mRNA and is eliminated by injecting synaptophysin or syntaxin antisense oligonucleotides. Additionally, botulinum toxins, which inactivate proteins involved in vesicle release and recycling, reduce basal GAT1 expression and prevent PKC-induced translocation. Mutant GAT1 proteins, in which most or all of a leucine heptad repeat sequence was removed, display altered basal distribution and lack susceptibility to modulation by PKC, delineating one region of GAT1 necessary for its targeting. Thus, functional regulation of GAT1 in oocytes occurs via components common to transporters and to trafficking in both neural and non-neural cells, and suggests a relationship between factors that control neurotransmitter secretion and the components necessary for neurotransmitter uptake

Second Messengers, Trafficking-Related Proteins, and Amino Acid Residues that Contribute to the Functional Regulation of the Rat Brain GABA Transporter GAT1

Recent evidence indicates that several members of the Na⁺-coupled transporter family are regulated, and this regulation in part occurs by redistribution of transporters between intracellular locations and the plasma membrane. We elucidate components of this process for both wild-type and mutant GABA transporters (GAT1) expressed in Xenopus oocytes using a combination of uptake assays, immunoblots, and electrophysiological measurements of membrane capacitance, transport-associated currents, and GAT1-specific charge movements. At low GAT1 expression levels, activators of protein kinase C (PKC) induce redistribution of GAT1 from intracellular vesicles to the plasma membrane; at higher GAT1 expression levels, activators of PKC fail to induce this redistribution. However, coinjection of total rat brain mRNA with GAT1 permits PKC-mediated modulation at high transporter expression levels. This effect of brain mRNA on modulation is mimicked by coinjection of syntaxin 1a mRNA and is eliminated by injecting synaptophysin or syntaxin antisense oligonucleotides. Additionally, botulinum toxins, which inactivate proteins involved in vesicle release and recycling, reduce basal GAT1 expression and prevent PKC-induced translocation. Mutant GAT1 proteins, in which most or all of a leucine heptad repeat sequence was removed, display altered basal distribution and lack susceptibility to modulation by PKC, delineating one region of GAT1 necessary for its targeting. Thus, functional regulation of GAT1 in oocytes occurs via components common to transporters and to trafficking in both neural and non-neural cells, and suggests a relationship between factors that control neurotransmitter secretion and the components necessary for neurotransmitter uptake

To which world regions does the valence–dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution.C.L. was supported by the Vienna Science and Technology Fund (WWTF VRG13-007); L.M.D. was supported by ERC 647910 (KINSHIP); D.I.B. and N.I. received funding from CONICET, Argentina; L.K., F.K. and Á. Putz were supported by the European Social Fund (EFOP-3.6.1.-16-2016-00004; ‘Comprehensive Development for Implementing Smart Specialization Strategies at the University of Pécs’). K.U. and E. Vergauwe were supported by a grant from the Swiss National Science Foundation (PZ00P1_154911 to E. Vergauwe). T.G. is supported by the Social Sciences and Humanities Research Council of Canada (SSHRC). M.A.V. was supported by grants 2016-T1/SOC-1395 (Comunidad de Madrid) and PSI2017-85159-P (AEI/FEDER UE). K.B. was supported by a grant from the National Science Centre, Poland (number 2015/19/D/HS6/00641). J. Bonick and J.W.L. were supported by the Joep Lange Institute. G.B. was supported by the Slovak Research and Development Agency (APVV-17-0418). H.I.J. and E.S. were supported by a French National Research Agency ‘Investissements d’Avenir’ programme grant (ANR-15-IDEX-02). T.D.G. was supported by an Australian Government Research Training Program Scholarship. The Raipur Group is thankful to: (1) the University Grants Commission, New Delhi, India for the research grants received through its SAP-DRS (Phase-III) scheme sanctioned to the School of Studies in Life Science; and (2) the Center for Translational Chronobiology at the School of Studies in Life Science, PRSU, Raipur, India for providing logistical support. K. Ask was supported by a small grant from the Department of Psychology, University of Gothenburg. Y.Q. was supported by grants from the Beijing Natural Science Foundation (5184035) and CAS Key Laboratory of Behavioral Science, Institute of Psychology. N.A.C. was supported by the National Science Foundation Graduate Research Fellowship (R010138018). We acknowledge the following research assistants: J. Muriithi and J. Ngugi (United States International University Africa); E. Adamo, D. Cafaro, V. Ciambrone, F. Dolce and E. Tolomeo (Magna Græcia University of Catanzaro); E. De Stefano (University of Padova); S. A. Escobar Abadia (University of Lincoln); L. E. Grimstad (Norwegian School of Economics (NHH)); L. C. Zamora (Franklin and Marshall College); R. E. Liang and R. C. Lo (Universiti Tunku Abdul Rahman); A. Short and L. Allen (Massey University, New Zealand), A. Ateş, E. Güneş and S. Can Özdemir (Boğaziçi University); I. Pedersen and T. Roos (Åbo Akademi University); N. Paetz (Escuela de Comunicación Mónica Herrera); J. Green (University of Gothenburg); M. Krainz (University of Vienna, Austria); and B. Todorova (University of Vienna, Austria). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.https://www.nature.com/nathumbehav/am2023BiochemistryGeneticsMicrobiology and Plant Patholog

Permeation Properties of Neurotransmitter Transporters

The neurotransmitter transporters belong to three known families of intrinsic membrane proteins (Figure 1). The energy for transport, which is often against the neurotransmitter concentration gradient, is derived from the cotransport (and in some cases the counter transport) of inorganic ions. Ion-transporting ATPases establish the concentration gradients for these ions

“Retention Projection” Enables Reliable Use of Shared Gas Chromatographic Retention Data Across Laboratories, Instruments, and Methods

Gas chromatography/mass spectrometry (GC/MS) is a primary tool used to identify compounds in complex samples. Both mass spectra and GC retention times are matched to those of standards; however, it is often impractical to have standards on hand for every compound of interest, so we must rely on shared databases of MS data and GC retention information. Unfortunately, retention databases (e.g., linear retention index libraries) are experimentally restrictive, notoriously unreliable, and strongly instrument dependent, relegating GC retention information to a minor, often negligible role in compound identification despite its potential power. A new methodology called “retention projection” has great potential to overcome the limitations of shared chromatographic databases. In this work, we tested the reliability of the methodology in five independent laboratories. We found that, even when each lab ran nominally the same method, the methodology was 3-fold more accurate than retention indexing because it properly accounted for unintentional differences between the GC/MS systems. When the laboratories used different methods of their own choosing, retention projections were 4- to 165-fold more accurate. More importantly, the distribution of error in the retention projections was <i>predictable</i> across different methods and laboratories, thus enabling automatic calculation of retention time tolerance windows. Tolerance windows at 99% confidence were generally narrower than those widely used even when physical standards are on hand to measure their retention. With its high accuracy and reliability, the new retention projection methodology makes GC retention a reliable, precise tool for compound identification, even when standards are not available to the user

“Retention Projection” Enables Reliable Use of Shared Gas Chromatographic Retention Data Across Laboratories, Instruments, and Methods

Gas chromatography/mass spectrometry (GC/MS) is a primary tool used to identify compounds in complex samples. Both mass spectra and GC retention times are matched to those of standards; however, it is often impractical to have standards on hand for every compound of interest, so we must rely on shared databases of MS data and GC retention information. Unfortunately, retention databases (e.g., linear retention index libraries) are experimentally restrictive, notoriously unreliable, and strongly instrument dependent, relegating GC retention information to a minor, often negligible role in compound identification despite its potential power. A new methodology called “retention projection” has great potential to overcome the limitations of shared chromatographic databases. In this work, we tested the reliability of the methodology in five independent laboratories. We found that, even when each lab ran nominally the same method, the methodology was 3-fold more accurate than retention indexing because it properly accounted for unintentional differences between the GC/MS systems. When the laboratories used different methods of their own choosing, retention projections were 4- to 165-fold more accurate. More importantly, the distribution of error in the retention projections was <i>predictable</i> across different methods and laboratories, thus enabling automatic calculation of retention time tolerance windows. Tolerance windows at 99% confidence were generally narrower than those widely used even when physical standards are on hand to measure their retention. With its high accuracy and reliability, the new retention projection methodology makes GC retention a reliable, precise tool for compound identification, even when standards are not available to the user