Novel mGluR- and CB1R-Independent Suppression of GABA Release Caused by a Contaminant of the Group I Metabotropic Glutamate Receptor Agonist, DHPG

Metabotropic glutamate receptors (mGluRs) are ubiquitous throughout the body, especially in brain, where they mediate numerous effects. MGluRs are classified into groups of which group I, comprising mGluRs 1 and 5, is especially important in neuronal communication. Group I actions are often investigated with the selective agonist, S-3,5-dihydroxyphenylglycine (DHPG). Despite the selectivity of DHPG, its use has often led to contradictory findings. We now report that a particular commercial preparation of DHPG can produce mGluR-independent effects. These findings may help reconcile some discrepant reports.We carried out electrophysiological recordings in the rat in vitro hippocampal slice preparation, focusing mainly on pharmacologically isolated GABA(A)-receptor-mediated synaptic currents.While preparations of DHPG from three companies suppressed GABAergic transmission in an mGluR-dependent way, one batch had an additional, unusual effect. Even in the presence of antagonists of mGluRs, it caused a reversible, profound suppression of inhibitory transmission. This mGluR-independent action was not due to a higher potency of the compound, or its ability to cause endocannabinoid-dependent responses. Field potential recordings revealed that glutamatergic transmission was not affected, and quantal analysis of GABA transmission confirmed the unusual effect was on GABA release, and not GABA(A) receptors. We have not identified the responsible factor in the DHPG preparation, but the samples were 99% pure as determined by HPLC and NMR analyses.In certain respects our observations with the anomalous batch strikingly resemble some published reports of unusual DHPG effects. The present findings could therefore contribute to explaining discrepancies in the literature. DHPG is widely employed to study mGluRs in different systems, hence rigorous controls should be performed before conclusions based on its use are drawn

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Inhibition of iLTD by CB1R antagonists.

<p>AM251 or SR141716A was present throughout all experiments. T-DHPG (T, white circles), Asc-08007-1-1, A, black circles). As T-DHPG caused no significant depression, recordings were stopped after 10 min of washout. Insets show representative traces for each condition. Black trace  =  baseline, dashed trace  =  DHPG, gray trace  = 25 min washout. Each trace is the average of ten consecutive responses. Peak eIPSC depression expressed as percent of baseline: T-DHPG 98.3±5.3%, n = 7, n.s.; Asc-08007-1-1: 53.6±8.7%, n = 6, p<0.01. Late eIPSC depressions (10-min washout); T-DHPG: 99.8±8.3%, n = 6, n.s.; Asc-08007-1-1: 57.5±7.6%, n = 6, p<0.05. Peak eIPSC was not significant from baseline after a 25 min washout of Asc-08007-1-1: 85.8±2.1%, n = 4, n.s. Cal. bars: y:100 pA, x: 50 ms.</p

Asc-08007-1-1 DHPG reduces frequency but not amplitude of asynchronous, evoked mIPSCs in the presence of mGluR antagonists.

<p>(A) Representative traces showing stimulation-evoked, asychronous mIPSCs in control conditions (Sr²⁺-substituted bathing solutions for all experiments; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0006122#s4" target="_blank">Materials and Methods</a>) (C), in DHPG (D) and after 10 min. of washout (W). Cal. bars: y: 13 pA, x: 40 ms. (B) Numbers of asynchronous evoked mIPSCs (white bars; counted in 31 traces per cell within a 150-ms window beginning 200 ms after a field stimulus in <i>s. radiatum</i>). Gray bars: frequency of spontaneous mIPSCs measured before stimulation (background). Events were counted in control condition (C), during DHPG application (D) and DHPG washout (W). Numbers of evoked mIPSCs (n = 6 cells); control: 30.2±5.6, DHPG: 21.2±5.9, Wash: 22.2±5.6. Numbers of background mIPSCs (same cells): control: 16.3±3.4 DHPG: 13.6±3.2; Wash: 14.5±6.4. Asterisks: significant differences from control evoked responses, p<0.05. No other groups differed by ANOVA followed by multiple t-tests. (C) Cumulative frequency of the amplitude distribution of evoked mIPSCs from one cell – control  =  white circles, DHPG  =  black circles, wash  =  gray triangles. Results typical of 6 of 7 cells analyzed. Inset: Average of superimposed traces (n = 53) of evoked mIPSCs before (control) and during DHPG application - C: Control, D: DHPG. Cal. bars: y: 8.6 pA, x: 13 ms.</p

Distinctive peaks in proton NMR spectrum of Asc-08007-1-1 DHPG.

<p>Segments of 1D proton NMR spectra derived from samples of Asc-08007-1-1 (A-007), Tocris DHPG, Sigma DHPG, and Asc-08116-5-3 (A-116). The samples were prepared in D₂O and the x-axis shows the chemical shifts in parts per million (ppm) with respect to the tetramethylsilane (TMS) reference signal at zero. The most striking difference between Asc-08007-1-1 and all other samples is the series of 4 doublets between about 7.2 and 8.2 ppm. The arrow in the top trace shows an enlargement of one of the doublets. Various organic molecules have chemical shifts in the range of 7.2 to 8.2 ppm, but the one responsible for the doublet pattern has not been identified. Not shown are the regions of the spectra between 0 and the water peak at 4.8 ppm in which irregular sequences of peaks were found in all samples. Each irregular sequence appeared to be unique for each preparation and did not obviously distinguish Asc-08007-1-1 from the others.</p

Asc-08007-1-1 DHPG does not affect fEPSPs in the presence of mGluR antagonists and gabazine.

<p>Traces in (A) and (B) show representative fEPSPs for each condition; NBQX and AP5 absent, and YM298198 and MPEP present for all experiments. Each trace (black  =  baseline, dashed  =  DHPG) is the average of 10 responses. (A) Left graph: raw amplitude measurement of fEPSPs before (control, n = 5) or during Asc-08007-1-1 application (DHPG, n = 5). Right graph: raw slope measurement of fEPSPs before (control, n = 5) or during DHPG application (DHPG, n = 5). (B) Same as in (A), but fEPSPs were recorded in the presence of gabazine, 20 µM. Left graph: raw amplitude measurement of fEPSPs before (control, n = 7) or during Asc-08007-1-1 application (DHPG, n = 7). Right graph: raw slope measurement of fEPSPs before (control, n = 7) or during Asc-08007-1-1 application (DHPG, n = 7, n.s.). Cal. bars: y: 0.1mV, x: 10 ms. Asterisk: significant difference, p<0.05, paired t-test.</p

Inhibition of DHPG-induced iLTD by group I mGluR antagonists.

<p>The selective mGluR1 antagonist, YM298198 (4 µM) and the mGluR5 antagonist, MPEP (10 µM), were present throughout all experiments. (A) For display and statistical comparison among groups, the data from T-DHPG and S-DHPG were pooled (white circles). As no significant depression was observed with these compounds, recordings were stopped after 10 min of washout. Peak eIPSC depressions as percent of baseline for each drug individually (data not shown): T-DHPG: 95.4±6.3%, n = 5, n.s.; S-DHPG: 93.9±1.8%, n = 3, n.s.; Asc-08007-1-1: 30.7±5.2%, n = 7, p<0.001. Late eIPSC depressions (after 10 min washout): T-DHPG: 100.3±9.8%, n = 4, n.s.; S-DHPG: 101.8±5.6%, n = 3, n.s.; Asc-08007-1-1: 40.6±4.1%, n = 7, p<0.001. After 25-min of washout, there was no significant depression caused by Asc-08007-1-1 DHPG (black circles): 85.5±4.8%, n = 7, n.s. Insets: Representative traces: black trace  =  baseline, dashed trace  =  DHPG, gray trace  = 25 min washout. Each trace is the average of ten consecutive responses; KGluc-based electrode solution was used (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0006122#s4" target="_blank">Materials and Methods</a>). Cal. bars: y:100 pA, x: 50 ms. (B) Continuous recorder trace showing the effects of T-DHPG, S-DHPG, and Asc-08007-1-1 DHPG sequentially applied, after washout of the previous appolication, to the same cell. A KCl-based electrode solution was used, so the eIPSCs are downward deflections that appear as straight lines at this time resolution. One-s voltage steps were given every 90 s to elicit Ca²⁺ influx through voltage-gated Ca²⁺ channels (VGCCs) and DSI <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0006122#pone.0006122-Fitzjohn1" target="_blank">[13]</a>, which appears as the transient reductions of eIPSCs. For display purposes, a small portion of the trace is omitted after each drug's washout. Note the strong remaining effect of Asc-08007-1-1, compared to the lack of effect of T-DHPG and S-DHPG. Cal. bars: y: 200 pA, x: 1 min.</p

Asc-08116-5-3 DHPG does not cause mGluR-independent effects.

<p>Representative traces (top) and pooled data (bottom) showing the effects of 50 µM Asc-08116-5-3 DHPG for 5 min on eIPSCs in slices pretreated in ω-agatoxin IVA (300 nM) and YM298198 plus MPEP. Traces (black  =  baseline, dashed  =  DHPG) are representative averages of 10 consecutive responses in each condition. Peak eIPSC amplitude depressions expressed as percent baseline amplitudes: Asc-08007-1-1(A-007): 28.5±5.9%, n = 5; T-DHPG (T): 80.2±10.0%, n = 4; S-DHPG (S): 85.3±4.9%, n = 3; Asc-08116-5-3 (A-116): 86.2±6.1%, n = 6. Asterisk: significant difference from baseline responses, p<0.05. Cal. bars: y:200 pA, x: 100 ms.</p

Concentration-response curves for Asc-08007-1-1 DHPG.

<p>Concentration-response curves in the presence (black circles) or absence (white circles) of mGluR antagonists (YM298198 plus MPEP, or LY341495 alone). Peak eIPSC amplitude depressions expressed as percent of baseline. Depression caused by all DHPG concentrations >1 µM are significant (p<0.01) in the presence and absence of antagonists. White circles: 1 µM: 89.9±2.5%, n = 4; 10 µM: 64.9±7.6%, n = 6; 20 µM: 38.8±4.3%, n = 6; 50 µM: 18.8±2.7%, n = 4. Black circles: 1 µM 96.4±3.3%, n = 4; 10 µM: 80.0±4.2%, n = 5; 20 µM: 63.8±1.3%, n = 6; 50 µM: 31.3±3.3%, n = 6. The difference between the depressions observed in the presence or absence of antagonists is significant for concentrations >10 µM (p<0.05).</p