T-type calcium channels play critical roles in cellular excitability and have been implicated in the pathogenesis of a variety of neurological disorders including epilepsy. Although there have been reports that certain neuroleptics that primarily target D₂dopamine receptors and are used to treat psychoses may also interact with T-type Ca channels, there has been no systematic examination of this phenomenon. In the present paper we provide a detailed analysis of the effects of several widely used neuroleptic agents on a family of exogenously expressed neuronal T-type Ca channels (α_1G, α_1H, and α_1Isubtypes). Among the neuroleptics tested, the diphenylbutylpiperidines pimozide and penfluridol were the most potent T-type channel blockers with K_d values (∼30–50 nm and ∼70–100 nm, respectively), in the range of their antagonism of the D₂ dopamine receptor. In contrast, the butyrophenone haloperidol was ∼12- to 20-fold less potent at blocking the various T-type Ca channels. The diphenyldiperazine flunarizine was also less potent compared with the diphenylbutylpiperadines and preferentially blocked α_1G and α_1I T-type channels compared with α_1H. The various neuroleptics did not significantly affect T-type channel activation or kinetic properties, although they shifted steady-state inactivation profiles to more negative values, indicating that these agents preferentially bind to channel inactivated states. Overall, our findings indicate that T-type Ca channels are potently blocked by a subset of neuroleptic agents and suggest that the action of these drugs on T-type Ca channels may significantly contribute to their therapeutic efficacy.

During the COVID-19 pandemic, the monitoring of SARS-CoV-2 RNA in wastewater was used to track the evolution and emergence of variant lineages and gauge infection levels in the community, informing appropriate public health responses without relying solely on clinical testing. As more sublineages were discovered, it increased the difficulty in identifying distinct variants in a mixed population sample, particularly those without a known lineage. Here, we compare the sequencing technology from Illumina and from Oxford Nanopore Technologies, in order to determine their efficacy at detecting variants of differing abundance, using 248 wastewater samples from various Quebec and Ontario cities. Our study used two analytical approaches to identify the main variants in the samples: the presence of signature and marker mutations and the co-occurrence of signature mutations within the same amplicon. We observed that each sequencing method detected certain variants at different frequencies as each method preferentially detects mutations of distinct variants. Illumina sequencing detected more mutations with a predominant lineage that is in low abundance across the population or unknown for that time period, while Nanopore sequencing had a higher detection rate of mutations that are predominantly found in the high abundance B.1.1.7 (Alpha) lineage as well as a higher sequencing rate of co-occurring mutations in the same amplicon. We present a workflow that integrates short-read and long-read sequencing to improve the detection of SARS-CoV-2 variant lineages in mixed population samples, such as wastewater.