The evolutionary expansion of sensory neuron populations detecting important environmental cues is widespread, but functionally enigmatic. We investigated this phenomenon through comparison of homologous neural pathways of Drosophila melanogaster and its close relative Drosophila sechellia, an extreme specialist for Morinda citrifolia noni fruit. D. sechellia has evolved species-specific expansions in select, noni-detecting olfactory sensory neuron (OSN) populations, through multigenic changes. Activation and inhibition of defined proportions of neurons demonstrate that OSN population increases contribute to stronger, more persistent, noni-odor tracking behavior. These sensory neuron expansions result in increased synaptic connections with their projection neuron (PN) partners, which are conserved in number between species. Surprisingly, having more OSNs does not lead to greater odor-evoked PN sensitivity or reliability. Rather, pathways with increased sensory pooling exhibit reduced PN adaptation, likely through weakened lateral inhibition. Our work reveals an unexpected functional impact of sensory neuron expansions to explain ecologically-relevant, species-specific behavior.

Understanding the cell-type composition and spatial organization of brain regions is crucial for interpreting brain computation and function. In the thalamus, the anterior thalamic nuclei (ATN) are involved in a wide variety of functions, yet the cell-type composition of the ATN remains unmapped at a single-cell and spatial resolution. Combining single-cell RNA sequencing, spatial transcriptomics, and multiplexed fluorescent in situ hybridization, we identify three discrete excitatory cell-type clusters that correspond to the known nuclei of the ATN and uncover marker genes, molecular pathways, and putative functions of these cell types. We further illustrate graded spatial variation along the dorsomedial-ventrolateral axis for all individual nuclei of the ATN and additionally demonstrate that the anteroventral nucleus exhibits spatially covarying protein products and long-range inputs. Collectively, our study reveals discrete and continuous cell-type organizational principles of the ATN, which will help to guide and interpret experiments on ATN computation and function.

Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins that become labeled in the presence of both a specific cellular activity and a fluorescent substrate. The recording period is set by the presence of the substrate, whereas the cellular activity controls the degree of the labeling. The use of distinguishable substrates enabled the recording of successive periods of activity. We recorded protein-protein interactions, G protein-coupled receptor activation, and increases in intracellular calcium. Recordings of elevated calcium levels allowed selections of cells from heterogeneous populations for transcriptomic analysis and tracking of neuronal activities in flies and zebrafish.

Spontaneously blinking fluorophores permit the detection and localization of individual molecules without reducing buffers or caging groups, thus simplifying single-molecule localization microscopy (SMLM). The intrinsic blinking properties of such dyes are dictated by molecular structure and modulated by environment, which can limit utility. We report a series of tuned spontaneously blinking dyes with duty cycles that span two orders of magnitude, allowing facile SMLM in cells and dense biomolecular structures.

Intracellular levels of the amino acid aspartate are responsive to changes in metabolism in mammalian cells and can correspondingly alter cell function, highlighting the need for robust tools to measure aspartate abundance. However, comprehensive understanding of aspartate metabolism has been limited by the throughput, cost, and static nature of the mass spectrometry (MS)-based measurements that are typically employed to measure aspartate levels. To address these issues, we have developed a green fluorescent protein (GFP)-based sensor of aspartate (jAspSnFR3), where the fluorescence intensity corresponds to aspartate concentration. As a purified protein, the sensor has a 20-fold increase in fluorescence upon aspartate saturation, with dose-dependent fluorescence changes covering a physiologically relevant aspartate concentration range and no significant off target binding. Expressed in mammalian cell lines, sensor intensity correlated with aspartate levels measured by MS and could resolve temporal changes in intracellular aspartate from genetic, pharmacological, and nutritional manipulations. These data demonstrate the utility of jAspSnFR3 and highlight the opportunities it provides for temporally resolved and high-throughput applications of variables that affect aspartate levels.

Although the dynamic instability of microtubules (MTs) is fundamental to many cellular functions, quiescent MTs with unattached free distal ends are commonly present and play important roles in various events to power cellular dynamics. However, how these free MT tips are stabilized remains poorly understood. Here, we report that centrosome and spindle pole protein 1 (CSPP1) caps and stabilizes both plus and minus ends of static MTs. Real-time imaging of laser-ablated MTs in live cells showed deposition of CSPP1 at the newly generated MT ends, whose dynamic instability was concomitantly suppressed. Consistently, MT ends in CSPP1-overexpressing cells were hyper-stabilized, while those in CSPP1-depleted cells were much more dynamic. This CSPP1-elicited stabilization of MTs was demonstrated to be achieved by suppressing intrinsic MT catastrophe and restricting the polymerization. Importantly, CSPP1-bound MTs were resistant to MCAK-mediated depolymerization. These findings delineate a previously uncharacterized CSPP1 activity that integrates MT end capping to orchestrate quiescent MTs.

Visualization of specific molecules and their assembly in real time and space is essential to delineate how cellular dynamics and signaling circuit are orchestrated during cell division cycle. Our recent studies reveal structural insights into human centromere-kinetochore core CCAN complex. Here we introduce a method for optically imaging trimeric and tetrameric protein interactions at nanometer spatial resolution in live cells using fluorescence complementation-based Förster resonance energy transfer (FC-FRET). Complementary fluorescent protein molecules were first used to visualize dimerization followed by FRET measurements. Using FC- FRET, we visualized centromere CENP-SXTW tetramer assembly dynamics in live cells, and dimeric interactions between CENP-TW dimer and kinetochore protein Spc24/25 dimer in dividing cells. We further delineated the interactions of monomeric CENP-T with Spc24/25 dimer in dividing cells. Surprisingly, our analyses revealed critical role of CDK1 kinase activity in the initial recruitment of Spc24/25 by CENP-T. However, interactions between CENP-T and Spc24/25 during chromosome segregation is independent of CDK1. Thus, FC-FRET provides a unique approach to delineate spatiotemporal dynamics of trimerized and tetramerized proteins at nanometer scale and establishes a platform to report the precise regulation of multimeric protein interactions in space and time in live cells.

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.

Representation learning in neural networks may be implemented with supervised or unsupervised algorithms, distinguished by the availability of feedback. In sensory cortex, perceptual learning drives neural plasticity, but it is not known if this is due to supervised or unsupervised learning. Here we recorded populations of up to 90,000 neurons simultaneously from the primary visual cortex (V1) and higher visual areas (HVA), while mice learned multiple tasks as well as during unrewarded exposure to the same stimuli. Similar to previous studies, we found that neural changes in task mice were correlated with their behavioral learning. However, the neural changes were mostly replicated in mice with unrewarded exposure, suggesting that the changes were in fact due to unsupervised learning. The neural plasticity was concentrated in the medial HVAs and obeyed visual, rather than spatial, learning rules. In task mice only, we found a ramping reward prediction signal in anterior HVAs, potentially involved in supervised learning. Our neural results predict that unsupervised learning may accelerate subsequent task learning, a prediction which we validated with behavioral experiments.

Many motor control systems generate multiple movements using a common set of muscles. How are premotor circuits able to flexibly generate diverse movement patterns? Here, we characterize the neuronal circuits that drive the distinct courtship songs of Drosophila melanogaster. Male flies vibrate their wings towards females to produce two different song modes – pulse and sine song – which signal species identity and male quality. Using cell-type specific genetic reagents and the connectome, we provide a cellular and synaptic map of the circuits in the male ventral nerve cord that generate these songs and examine how activating or inhibiting each cell type within these circuits affects the song. Our data reveal that the song circuit is organized into two nested feed-forward pathways, with extensive reciprocal and feed-back connections. The larger network produces pulse song, the more complex and ancestral song form. A subset of this network produces sine song, the simpler and more recent form. Such nested organization may be a common feature of motor control circuits in which evolution has layered increasing flexibility on to a basic movement pattern.