Biology subjects

Currier, T. A.

Publications and source records attributed to Currier, T. A..

6 recordsLinked to original sources

bioRxiv2026

Unilateral gene expression via maternally controlled zygotic recombination in Drosophila

Structural and functional asymmetries are ubiquitous in bilaterians, but tools for unilateral genetic access have been lacking, a methodological gap that has limited mechanistic dissections of lateralized cellular functions. We developed the Maternally Controlled Zygotic Recombination (MCZR) system to overcome this limitation in Drosophila, co-opting the regulatory machinery of the maternal-to-zygotic transition to enable somatic recombination during early embryonic development. Targeting recombinase activity to this early window generates large somatic mosaics that frequently split across the anatomical midline. In conjunction with cell type-specific driver lines, this approach provides a reliable, scalable, and user-friendly platform for unilateral transgene expression. In proof-of-concept experiments, we apply our tool to the question of locomotor control, illustrating how MCZR can be used to unilaterally manipulate or monitor a cell type of interest. Overall, the MCZR system unlocks previously inaccessible experimental avenues across neuroscience, cell biology, and developmental biology.

neuroscience↗

bioRxiv2026

Branch-specific axon pruning induced by Dpr4/DIP-{Theta} transneuronal interactions

Neuronal remodeling is a conserved, late developmental mechanism to refine neural circuits. Although remodeling typically occurs with remarkable spatiotemporal precision, its underlying molecular mechanisms remain poorly understood. In the Drosophila mushroom body (MB) circuit, {gamma}-Kenyon cells ({gamma}-KCs) undergo stereotyped remodeling during metamorphosis, in which they prune their larval vertical and medial axonal branches and subsequently regrow a medial, adult-specific branch. Our previous transcriptional profiling of developing {gamma}-KCs revealed dynamic expression of Defective proboscis extension response (Dpr) proteins and their binding partners, Dpr-interacting proteins (DIPs), members of the Immunoglobulin (Ig) superfamily. Despite their established roles in neurodevelopment, how Dpr/DIPs function - given their lack of intracellular domains - remains unclear. Here, we show that overexpression of Dpr4 in developing {gamma}-KCs cell-autonomously inhibits axon pruning. Strikingly, this effect is branch-specific: the vertical axonal branch fails to prune, while the medial branch prunes normally. To our knowledge, this represents the first demonstration of branch-specific control of pruning in this system. Moreover, the adult medial branch regrows normally, indicating that pruning and regrowth are independently regulated at the level of individual branches. We demonstrate that this unique branch-specificity arises from trans-neuronal interactions between Dpr4 in {gamma}-KCs and DIP-{theta} in dopaminergic neurons that selectively innervate the vertical larval MB lobe. Furthermore, our findings suggest that this phenotype relies on an Ig2 domain of a Dpr family member, implying the involvement of a third binding partner. Leveraging this robust overexpression phenotype to probe downstream mechanisms, we find that loss of the transmembrane adhesion protein N-Cadherin suppresses the Dpr4-induced pruning defect. Together, our findings highlight the local impact of Dpr/DIP-mediated trans-neuronal interactions on the spatial regulation of remodeling, and provide genetic evidence implicating N-Cadherin as a potential downstream mediator of Dpr/DIP function within a developing neural circuit.

neuroscience↗

bioRxiv2025

Infrequent strong connections constrain connectomic predictions of neuronal function

How does circuit wiring constrain neural computation? Recent work has leveraged connectomic datasets to predict the function of cells and circuits in the brains of many species. However, many of these hypotheses have not been compared with physiological measurements, obscuring the limits of connectome-based functional predictions. To explore these limits, we characterized the visual responses of 91 cell types in the fruit fly and quantitatively compared them to connectomic predictions. We show that these predictions are accurate for some response properties, such as orientation tuning, but are surprisingly poor for other properties, such as receptive field size. Importantly, strong synaptic inputs are more functionally homogeneous than expected by chance, and exert an outsized influence on postsynaptic responses, providing a powerful modeling constraint. Finally, we show that physiology is a stronger predictor of wiring than wiring is of physiology, revising our understanding of the structure-function relationship in the brain.

neuroscience↗

bioRxiv2021

A neural circuit for wind-guided olfactory navigation

To navigate towards a food source, animals must frequently combine odor cues that tell them what sources are useful with wind direction cues that tell them where the source can be found. Where and how these two cues are integrated to support navigation is unclear. Here we identify a pathway to the Drosophila fan-shaped body (FB) that encodes attractive odor and promotes upwind navigation. We show that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, we identify FB local neurons called h{Delta}C that receive input from this odor pathway and a previously described wind pathway. We show that h{Delta}C neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h{Delta}C neurons promotes navigation in a reproducible direction, and that h{Delta}C activity is required for persistent upwind orientation during odor. Based on connectome data, we develop a computational model showing how h{Delta}C activity can promote navigation towards a goal such as an upwind odor source. Our results suggest that odor and wind cues are processed by separate pathways and integrated within the FB to support goal-directed navigation.

neuroscience↗

bioRxiv2019

A neural circuit basis for context-modulation of individual locomotor behavior

Defying the cliche that biological variation arises from differences in nature or nurture, genetically identical animals reared in the same environment exhibit striking differences in their behaviors. Innate behaviors can be surprisingly flexible, for example by exhibiting context-dependence. The intersection of behavioral individuality and context-dependence is largely unexplored, particularly at the neural circuit level. Here, we show that individual flies tendencies to turn left or right (locomotor handedness) changes when ambient illumination changes. This change is itself a stable individual behavioral characteristic. Silencing output neurons of the central complex (a premotor area that mediates goal-directed navigation) blocks this change. These neurons respond to light with idiosyncratic changes to their baseline calcium levels, and idiosyncratic morphological variation in their presynaptic arbors correlates with idiosyncratic sensory-context-specific turn biases. These findings provide a circuit mechanism by which individual locomotor biases arise and are modulated by sensory context.

neuroscience↗

bioRxiv2018

Dynamic integration of multisensory turn commands supports active reorienting during ongoing navigation.

A longstanding goal of systems neuroscience is to quantitatively describe how the brain integrates cues from multiple modalities over time. Here we develop a closed-loop orienting paradigm in Drosophila to study the algorithms by which stimuli from different modalities are combined during ongoing navigation. We show that flies faced with an attractive visual and an aversive mechanosensory cue exhibit sequential responses, first turning away from the co-localized stimuli before turning back toward them. We also find that the presence of the aversive cue slows flies turns toward the attractive target, suggesting that conflicting unimodal turn commands are summed to produce multisensory turns of intermediate velocity. We then test a series of computational frameworks and find that integration is best described by a model in which multimodal stimuli are continuously and dynamically scaled, converted into turn commands, and then summed to produce ongoing orientation behavior.

neuroscience↗