Elevating levels of the endocannabinoid 2-arachidonoylglycerol blunts opioid reward but not analgesia

Converging findings have established that the endocannabinoid (eCB) system serves as a possible target for the development of new treatments for pain as a complement to opioid-based treatments. Here we show in male and female mice that enhancing levels of the eCB, 2-arachidonoylglycerol (2-AG), through pharmacological inhibition of its catabolic enzyme, monoacylglycerol lipase (MAGL), either systemically or in the ventral tegmental area (VTA) with JZL184, leads to a substantial attenuation of the rewarding effects of opioids in male and female mice using conditioned place preference and self-administration paradigms, without altering their analgesic properties. These effects are driven by CB1 receptors (CB1Rs) within the VTA as VTA CB1R conditional knockout, counteracts JZL184's effects. Conversely, pharmacologically enhancing the levels of the other eCB, anandamide (AEA), by inhibition of fatty acid amide hydrolase (FAAH) has no effect on opioid reward or analgesia. Using fiber photometry with fluorescent sensors for calcium and dopamine (DA), we find that enhancing 2-AG levels diminishes opioid reward-related nucleus accumbens (NAc) activity and DA neurotransmission. Together these findings reveal that 2-AG counteracts the rewarding properties of opioids and provides a potential adjunctive therapeutic strategy for opioid-related analgesic treatments.

Adolescents flexibly adapt action selection based on controllability inferences

From early in life, we encounter both controllable environments, in which our actions can causally influence the reward outcomes we experience, and uncontrollable environments, in which they cannot. Environmental controllability is theoretically proposed to organize our behavior. In controllable contexts, we can learn to proactively select instrumental actions that bring about desired outcomes. In uncontrollable environments, Pavlovian learning enables hard-wired, reflexive reactions to anticipated, motivationally salient events, providing "default" behavioral responses. Previous studies characterizing the balance between Pavlovian and instrumental learning systems across development have yielded divergent findings, with some studies observing heightened expression of Pavlovian learning during adolescence and others observing a reduced influence of Pavlovian learning during this developmental stage. In this study, we aimed to investigate whether a theoretical model of controllability-dependent arbitration between learning systems might explain these seemingly divergent findings in the developmental literature, with the specific hypothesis that adolescents' action selection might be particularly sensitive to environmental controllability. To test this hypothesis, 90 participants, aged 8-27, performed a probabilistic-learning task that enables estimation of Pavlovian influence on instrumental learning, across both controllable and uncontrollable conditions. We fit participants' data with a reinforcement-learning model in which controllability inferences adaptively modulate the dominance of Pavlovian versus instrumental control. Relative to children and adults, adolescents exhibited greater flexibility in calibrating the expression of Pavlovian bias to the degree of environmental controllability. These findings suggest that sensitivity to environmental reward statistics that organize motivated behavior may be heightened during adolescence.

ScISOr-ATAC reveals convergent and divergent splicing and chromatin specificities between matched cell types across cortical regions, evolution, and in Alzheimer's Disease

Multimodal measurements have become widespread in genomics, however measuring open chromatin accessibility and splicing simultaneously in frozen brain tissues remains unconquered. Hence, we devised Single-Cell-ISOform-RNA sequencing coupled with the Assay-for-Transposase-Accessible-Chromatin (ScISOr-ATAC). We utilized ScISOr-ATAC to assess whether chromatin and splicing alterations in the brain convergently affect the same cell types or divergently different ones. We applied ScISOr-ATAC to three major conditions: comparing (i) the Rhesus macaque (Macaca mulatta) prefrontal cortex (PFC) and visual cortex (VIS), (ii) cross species divergence of Rhesus macaque versus human PFC, as well as (iii) dysregulation in Alzheimer's disease in human PFC. We found that among cortical-layer biased excitatory neuron subtypes, splicing is highly brain-region specific for L3-5/L6 IT_RORB neurons, moderately specific in L2-3 IT_CUX2.RORB neurons and unspecific in L2-3 IT_CUX2 neurons. In contrast, at the chromatin level, L2-3 IT_CUX2.RORB neurons show the highest brain-region specificity compared to other subtypes. Likewise, when comparing human and macaque PFC, strong evolutionary divergence on one molecular modality does not necessarily imply strong such divergence on another molecular level in the same cell type. Finally, in Alzheimer's disease, oligodendrocytes show convergently high dysregulation in both chromatin and splicing. However, chromatin and splicing dysregulation most strongly affect distinct oligodendrocyte subtypes. Overall, these results indicate that chromatin and splicing can show convergent or divergent results depending on the performed comparison, justifying the need for their concurrent measurement to investigate complex systems. Taken together, ScISOr-ATAC allows for the characterization of single-cell splicing and chromatin patterns and the comparison of sample groups in frozen brain samples.

From words to complete phrases: insight into single-cell isoforms using short and long reads

The profiling of gene expression patterns to glean biological insights from single cells has become commonplace over the last few years. However, this approach overlooks the transcript contents that can differ between individual cells and cell populations. In this review, we describe early work in the field of single-cell short-read sequencing as well as full-length isoforms from single cells. We then describe recent work in single-cell long-read sequencing wherein some transcript elements have been observed to work in tandem. Based on earlier work in bulk tissue, we motivate the study of combination patterns of other RNA variables. Given that we are still blind to some aspects of isoform biology, we suggest possible future avenues such as CRISPR screens which can further illuminate the function of RNA variables in distinct cell populations.

Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue

Single-nuclei RNA sequencing characterizes cell types at the gene level. However, compared to single-cell approaches, many single-nuclei cDNAs are purely intronic, lack barcodes and hinder the study of isoforms. Here we present single-nuclei isoform RNA sequencing (SnISOr-Seq). Using microfluidics, PCR-based artifact removal, target enrichment and long-read sequencing, SnISOr-Seq increased barcoded, exon-spanning long reads 7.5-fold compared to naive long-read single-nuclei sequencing. We applied SnISOr-Seq to adult human frontal cortex and found that exons associated with autism exhibit coordinated and highly cell-type-specific inclusion. We found two distinct combination patterns: those distinguishing neural cell types, enriched in TSS-exon, exon-polyadenylation-site and non-adjacent exon pairs, and those with multiple configurations within one cell type, enriched in adjacent exon pairs. Finally, we observed that human-specific exons are almost as tightly coordinated as conserved exons, implying that coordination can be rapidly established during evolution. SnISOr-Seq enables cell-type-specific long-read isoform analysis in human brain and in any frozen or hard-to-dissociate sample.

Developmental shifts in computations used to detect environmental controllability

Accurate assessment of environmental controllability enables individuals to adaptively adjust their behavior—exploiting rewards when desirable outcomes are contingent upon their actions and minimizing costly deliberation when their actions are inconsequential. However, it remains unclear how estimation of environmental controllability changes from childhood to adulthood. Ninety participants (ages 8–25) completed a task that covertly alternated between controllable and uncontrollable conditions, requiring them to explore different actions to discover the current degree of environmental controllability. We found that while children were able to distinguish controllable and uncontrollable conditions, accuracy of controllability assessments improved with age. Computational modeling revealed that whereas younger participants’ controllability assessments relied on evidence gleaned through random exploration, older participants more effectively recruited their task structure knowledge to make highly informative interventions. Age-related improvements in working memory mediated this qualitative shift toward increased use of an inferential strategy. Collectively, these findings reveal an age-related shift in the cognitive processes engaged to assess environmental controllability. Improved detection of environmental controllability may foster increasingly adaptive behavior over development by revealing when actions can be leveraged for one’s benefit.

The ability to determine when one’s actions are consequential organizes learning and decision making across the lifespan. However, few studies have examined how the ability to detect control over our environment changes from childhood to adulthood. Here, we leveraged a computational modeling framework to characterize the component learning processes underlying controllability assessment in children, adolescents, and adults. We observed age-related improvements in controllability assessment that stemmed from an increasing ability to represent contingencies between states and actions and to use that knowledge to make informative interventions that yield diagnostic evidence of the current degree of control. Increasing ability to accurately assess environmental controllability may confer greater recognition of opportunities to adaptively pursue rewards through goal-directed action across development.