Molecular neurobiology of loss: a role for basolateral amygdala extracellular matrix.

Psychological loss is a common experience that erodes well-being and negatively impacts quality of life. The molecular underpinnings of loss are poorly understood. Here, we investigate the mechanisms of loss using an environmental enrichment removal (ER) paradigm in male rats. The basolateral amygdala (BLA) was identified as a region of interest, demonstrating differential Fos responsivity to ER and having an established role in stress processing and adaptation. A comprehensive multi-omics investigation of the BLA, spanning multiple cohorts, platforms, and analyses, revealed alterations in microglia and the extracellular matrix (ECM). Follow-up studies indicated that ER decreased microglia size, complexity, and phagocytosis, suggesting reduced immune surveillance. Loss also substantially increased ECM coverage, specifically targeting perineuronal nets surrounding parvalbumin interneurons, suggesting decreased plasticity and increased inhibition within the BLA following loss. Behavioral analyses suggest that these molecular effects are linked to impaired BLA salience evaluation, leading to a mismatch between stimulus and reaction intensity. These loss-like behaviors could be rescued by depleting BLA ECM during the removal period, helping us understand the mechanisms underlying loss and revealing novel molecular targets to ameliorate its impact.

Using protein turnover to expand the applications of transcriptomics.

RNA expression and protein abundance are often at odds when measured in parallel, raising questions about the functional implications of transcriptomics data. Here, we present the concept of persistence, which attempts to address this challenge by combining protein half-life data with RNA expression into a single metric that approximates protein abundance. The longer a protein's half-life, the more influence it can have on its surroundings. This data offers a valuable opportunity to gain deeper insight into the functional meaning of transcriptome changes. We demonstrate the application of persistence using schizophrenia (SCZ) datasets, where it greatly improved our ability to predict protein abundance from RNA expression. Furthermore, this approach successfully identified persistent genes and pathways known to have impactful changes in SCZ. These results suggest that persistence is a valuable metric for improving the functional insight offered by transcriptomics data, and extended application of this concept could advance numerous research fields.