An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single cells.

High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single cells. However, conventional fluorescent protein (FP) modifications used to discriminate single cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and nondeleterious nuclear localization signal (NLS) tag strategy, called "Arginine-rich NLS" (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes and in response to both local and systemic brain-wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances machine learning-automated segmentation of single cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single cells at scale and paired with behavioral procedures.

Incubation of palatable food craving is associated with brain-wide neuronal activation in mice.

Studies using rodent models have shown that relapse to drug or food seeking increases progressively during abstinence, a behavioral phenomenon termed "incubation of craving." Mechanistic studies of incubation of craving have focused on specific neurobiological targets within preselected brain areas. Recent methodological advances in whole-brain immunohistochemistry, clearing, and imaging now allow unbiased brain-wide cellular resolution mapping of regions and circuits engaged during learned behaviors. However, these whole-brain imaging approaches were developed for mouse brains, while incubation of drug craving has primarily been studied in rats, and incubation of food craving has not been demonstrated in mice. Here, we established a mouse model of incubation of palatable food craving and examined food reward seeking after 1, 15, and 60 abstinence days. We then used the neuronal activity marker Fos with intact-brain mapping procedures to identify corresponding patterns of brain-wide activation. Relapse to food seeking was significantly higher after 60 abstinence days than after 1 or 15 days. Using unbiased ClearMap analysis, we identified increased activation of multiple brain regions, particularly corticostriatal structures, following 60 but not 1 or 15 abstinence days. We used orthogonal SMART2 analysis to confirm these findings within corticostriatal and thalamocortical subvolumes and applied expert-guided registration to investigate subdivision and layer-specific activation patterns. Overall, we 1) identified brain-wide activity patterns during incubation of food seeking using complementary analytical approaches and 2) provide a single-cell resolution whole-brain atlas that can be used to identify functional networks and global architecture underlying the incubation of food craving.

Distributed X chromosome inactivation in brain circuitry is associated with X-linked disease penetrance of behavior.

The precise anatomical degree of brain X chromosome inactivation (XCI) that is sufficient to alter X-linked disorders in females is unclear. Here, we quantify whole-brain XCI at single-cell resolution to discover a prevalent activation ratio of maternal to paternal X at 60:40 across all divisions of the adult brain. This modest, non-random XCI influences X-linked disease penetrance: maternal transmission of the fragile X mental retardation 1 (Fmr1)-knockout (KO) allele confers 55% of total brain cells with mutant X-active, which is sufficient for behavioral penetrance, while 40% produced from paternal transmission is tolerated. Local XCI mosaicism within affected maternal Fmr1-KO mice further specifies sensorimotor versus social anxiety phenotypes depending on which distinct brain circuitry is most affected, with only a 50%-55% mutant X-active threshold determining penetrance. Thus, our results define a model of X-linked disease penetrance in females whereby distributed XCI among single cells populating brain circuitries can regulate the behavioral penetrance of an X-linked mutation.

Distinct dynamics and intrinsic properties in ventral tegmental area populations mediate reward association and motivation.

Ventral tegmental area (VTA) dopamine neurons regulate reward-related associative learning and reward-driven motivated behaviors, but how these processes are coordinated by distinct VTA neuronal subpopulations remains unresolved. Here, we compare the contribution of two primarily dopaminergic and largely non-overlapping VTA subpopulations, all VTA dopamine neurons and VTA GABAergic neurons of the mouse midbrain, to these processes. We find that the dopamine subpopulation that projects to the nucleus accumbens (NAc) core preferentially encodes reward-predictive cues and prediction errors. In contrast, the subpopulation that projects to the NAc shell preferentially encodes goal-directed actions and relative reward anticipation. VTA GABA neuron activity strongly contrasts VTA dopamine population activity and preferentially encodes reward outcome and retrieval. Electrophysiology, targeted optogenetics, and whole-brain input mapping reveal multiple convergent sources that contribute to the heterogeneity among VTA dopamine subpopulations that likely underlies their distinct encoding of reward-related associations and motivation that defines their functions in these contexts.

Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience.

The study of complex behaviors is often challenging when using manual annotation due to the absence of quantifiable behavioral definitions and the subjective nature of behavioral annotation. Integration of supervised machine learning approaches mitigates some of these issues through the inclusion of accessible and explainable model interpretation. To decrease barriers to access, and with an emphasis on accessible model explainability, we developed the open-source Simple Behavioral Analysis (SimBA) platform for behavioral neuroscientists. SimBA introduces several machine learning interpretability tools, including SHapley Additive exPlanation (SHAP) scores, that aid in creating explainable and transparent behavioral classifiers. Here we show how the addition of explainability metrics allows for quantifiable comparisons of aggressive social behavior across research groups and species, reconceptualizing behavior as a sharable reagent and providing an open-source framework. We provide an open-source, graphical user interface (GUI)-driven, well-documented package to facilitate the movement toward improved automation and sharing of behavioral classification tools across laboratories.

An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single-cells.

High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single-cells. However, conventional fluorescent protein (FP) modifications used to discriminate single-cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and non-deleterious nuclear localization signal (NLS) tag strategy, called 'Arginine-rich NLS' (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single-cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes, and in response to both local and systemic brain wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances ML-automated segmentation of single-cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single-cells at scale and paired with behavioral procedures.

Time-course analysis of injured skeletal muscle suggests a critical involvement of ERK1/2 signaling in the acute inflammatory response.

INTRODUCTION: The coupling and timing of pro- and anti-inflammatory processes in skeletal muscle injury is poorly understood. We investigated the temporal response and regulated processes of extracellular signal-regulated kinases 1 and 2 (ERK1/2), p38, and IkappaB kinase (IKK) α/ß signaling pathways after traumatic injury. METHODS: Traumatic freeze injury was delivered to the tibialis anterior (TA) muscle in C57BL/6J mice, and injured and uninjured TA muscles were analyzed 3-72 h into the recovery period. RESULTS: Significant increases in pro-inflammatory cytokine transcription accompanied IKKß phosphorylation, robust ERK pathway activation, and reduced heat shock protein (Hsp) protein expression at 3-24 h. At 24 h, ERK activation was abolished concomitantly with a significant increase in mitogen-activated protein kinase phosphatase-1 (MKP-1). After 24 h, cytokine transcription along with ERK1/2 and IKKß phosphorylation remained suppressed, whereas Hsp protein expression rose to significant levels by 72 h and associated with IKKß. CONCLUSIONS: Results indicate a bimodal regulation of ERK1/2 in acute inflammation in which it is supportive from 3 to 24 h, and suppressive from 24 to 72 h.

Enhancer viruses for combinatorial cell-subclass-specific labeling.

Rapid cell type identification by new genomic single-cell analysis methods has not been met with efficient experimental access to these cell types. To facilitate access to specific neural populations in mouse cortex, we collected chromatin accessibility data from individual cells and identified enhancers specific for cell subclasses and types. When cloned into recombinant adeno-associated viruses (AAVs) and delivered to the brain, these enhancers drive transgene expression in specific cortical cell subclasses. We extensively characterized several enhancer AAVs to show that they label different projection neuron subclasses as well as a homologous neuron subclass in human cortical slices. We also show how coupling enhancer viruses expressing recombinases to a newly generated transgenic mouse, Ai213, enables strong labeling of three different neuronal classes/subclasses in the brain of a single transgenic animal. This approach combines unprecedented flexibility with specificity for investigation of cell types in the mouse brain and beyond.

Matrix metalloprotease-3 and tissue inhibitor of metalloprotease-1 mRNA and protein levels are altered in response to traumatic skeletal muscle injury.

The purpose of this study was to characterize the time course of matrix metalloprotease-3 (MMP-3) and tissue inhibitor of metalloprotease-1 (TIMP-1) expression in mouse tibialis anterior (TA) muscle post-injury. Mice were anesthetized, the TA muscle exposed, and injury induced by applying a cold steel probe (-79 degrees C) to the muscle for 10 s. Muscle was collected from uninjured and injured legs at 3, 10, 24, 48, and 72 h post-injury. qRT-PCR, immunoblotting, and immunohistochemistry were used to quantify/localize MMP-3 and TIMP-1. MMP-3 transcripts increased 19- and 12-fold, 10 and 24 h post-injury (p < 0.01), respectively. TIMP-1 transcript levels increased 9-, 34-, and 60-fold, 10, 24, and 48 h post-injury (p = 0.01), respectively, with a subsequent decrease 72 h post-injury (p < 0.01). Protein levels of the pro-form of MMP-3 increased within 3 h post-injury and remained elevated (p < 0.05). Active MMP-3 decreased over time, reaching a 72% decrease 72 h post-injury (p < 0.05). TIMP-1 protein decreased 75% within 3 h post-injury, returning to baseline by 72 h post-injury. In response to injury, injured skeletal muscle preferentially produces increased levels of the latent form of the MMP-3 protein with a concomitant decrease in the active form, and a significant decrease in TIMP-1 expression. The altered pattern of MMP-3/TIMP-1 expression may be due to alterations in post-transcriptional mechanisms that are responsible for specific regulation of the MMP-3/TIMP-1 system. These data suggest that there is a disproportionate regulation of the MMP-3/TIMP-1 system following traumatic injury and this response may contribute to impaired extracellular matrix remodeling.

Alterations in mRNA and protein levels of metalloproteinases-2, -9, and -14 and tissue inhibitor of metalloproteinase-2 responses to traumatic skeletal muscle injury.

This study characterizes the temporal relationship of membrane type-1 matrix metalloproteinase (MT1-MMP) and tissue inhibitor of metalloproteinase-2 (TIMP-2) expression in skeletal muscle following injury. Tibialis anterior (TA) muscles from 60 mice were exposed and injured by applying a cold steel probe (-79 degrees C) to the muscle for 10 s. Thereafter, TA muscles from uninjured and injured legs were collected at 3, 10, 24, 48, and 72 h postinjury for analysis of local MT1-MMP, TIMP-2, and matrix metalloproteinases-2 and -9 (MMP-2 and MMP-9) mRNA and protein content via quantitative RT-PCR, immunoblotting, zymography, and immunofluorescence. All data are expressed as fold change of injured leg vs. uninjured leg. MT1-MMP mRNA levels were decreased significantly at 48 and 72 h postinjury by approximately 9- and 21-fold, respectively (P < 0.01). Both TIMP-2 and MMP-2 mRNA expression significantly decreased in the injured leg by approximately 4- to 10-fold at 10-72 h postinjury (P < 0.01). MMP-9 mRNA expression was significantly increased at 10, 24, and 48 h postinjury by 6- (P < 0.05), 25-, and 12-fold (P < 0.01), respectively. Protein content of latent (63 kDa) MT1-MMP was decreased at 48 and 72 h postinjury by approximately 2-fold (P < 0.01). Content of the soluble (50 kDa) fragment of MT1-MMP was significantly increased by approximately 17-, 25-, and 67-fold at 24 (P < 0.05), 48, and 72 h (P < 0.01) postinjury, respectively. TIMP-2 protein levels diminished from 3 to 48 h postinjury by 1.5-fold to 1.8-fold (P < 0.01), before returning to baseline levels at 72 h postinjury. Zymography revealed visual increases in gelatinase activity in molecular weight regions corresponding to MMP-9 and MMP-2. In conclusion, skeletal muscle injury initiates a sequence of events in the MT1-MMP proteolytic cascade resulting in elevated levels of the soluble (50 kDa) fragment of MT1-MMP, which could enhance pericellular extracellular matrix remodeling.