impact protein function and localization, largely via modulating membrane affi nity and protein stability (7)(8)(9). In contrast to the stable thioether linkage of S -prenylation, the thioester linkage of S -acylation confers a reversible and dynamic nature on this modifi cation, and many recent efforts are shedding light on how this modifi cation is regulated ( 8-11 ).There are a variety of methodologies to detect protein S -acylation/palmitoylation in intact cells. A well-established method involves incubating cells with 3 H-labeled palmitate, followed by autoradiography to visualize the degree of isotopic incorporation. However, this approach requires high levels of [ 3 H]palmitate (as many as several mCi per sample) and exposure times on the order of weeks ( 12, 13 ). More recent methods have cleverly circumvented these issues by using nonradioactive derivatives of palmitate, which can be enriched or detected via cycloaddition reactions ( "click chemistry") ( 14-17 ). Nonetheless, these "palmitate-centric" approaches are encumbered by i ) the need for radioactive or chemically modifi ed palmitate analogs; ii ) the likely bias for proteins that undergo rapid palmitate turnover versus proteins that are more stably palmitoylated; iii ) diffi culty in detecting individual S -acylated proteins or their specifi c sites of S -acylation; and iv ) the inability to detect proteins that are acylated with moieties other than palmitate (e.g., shorter, longer, or unsaturated lipid chains).Recently, a "cysteine-centric" approach to identify S -acylated proteins was introduced that uses the conversion of the protein thioester to a disulfi de-linked biotin ( 18, 19 ). This assay, known as acyl-biotin exchange (ABE), is readily Abstract Protein S -acylation is a major posttranslational modifi cation whereby a cysteine thiol is converted to a thioester. A prototype is S -palmitoylation (fatty acylation), in which a protein undergoes acylation with a hydrophobic 16 carbon lipid chain. Although this modifi cation is a well-recognized determinant of protein function and localization, current techniques to study cellular S -acylation are cumbersome and/or technically demanding. We recently described a simple and robust methodology to rapidly identify S -nitrosylation sites in proteins via resin-assisted capture (RAC) and provided an initial description of the applicability of the technique to S -acylated proteins (acyl-RAC). Here we expand on the acyl-RAC assay, coupled with mass spectrometry-based proteomics, to characterize both previously reported and novel sites of endogenous S -acylation. Acyl-RAC should therefore fi nd general applicability in studies of both global and individual protein S -acylation in mammalian cells. Supplementary key words acylation • H-Ras • lipid • palmitoylation • proteomicsProtein cysteine residues undergo a wide variety of chemical reactions owing to thiol nucleophilicity and redox reactivity. These reactions include S -nitrosylation ( 1, 2 ), S -prenylation ( 3, 4 ), and S -acylation ( 5, 6 ), wh...

Summary Brain-wide fluctuations in local field potential oscillations reflect emergent network-level signals that mediate behavior. Cracking the code whereby these oscillations coordinate in time and space (spatiotemporal dynamics) to represent complex behaviors would provide fundamental insights into how the brain signals emotional pathology. Using machine learning, we discover a spatiotemporal dynamic network that predicts the emergence of major depressive disorder (MDD)-related behavioral dysfunction in mice subjected to chronic social defeat stress. Activity patterns in this network originate in prefrontal cortex and ventral striatum, relay through amygdala and ventral tegmental area, and converge in ventral hippocampus. This network is increased by acute threat, and it is also enhanced in three independent models of MDD vulnerability. Finally, we demonstrate that this vulnerability network is biologically distinct from the networks that encode dysfunction after stress. Thus, these findings reveal a convergent mechanism through which MDD vulnerability is mediated in the brain.

Summary Circuits distributed across cortico-limbic brain regions compose the networks that mediate emotional behavior. The prefrontal cortex (PFC) regulates ultraslow (<1Hz) dynamics across these networks, and PFC dysfunction is implicated in stress-related illnesses including major depressive disorder (MDD). To uncover the mechanism whereby stress-induced changes in PFC circuitry alter emotional networks to yield pathology, we used a multi-disciplinary approach including in vivo recordings in mice and chronic social-defeat stress. Our network model, inferred using machine learning, linked stress-induced behavioral pathology to the capacity of PFC to synchronize amygdala and VTA activity. Direct stimulation of PFC-amygdala circuitry with DREADDs normalized PFC-dependent limbic synchrony in stress-susceptible animals and restored normal behavior. In addition to providing insights into MDD mechanisms, our findings demonstrate an interdisciplinary approach that can be used to identify the large-scale network changes that underlie complex emotional pathologies and the specific network nodes that can be used to develop targeted interventions.