Single-stranded DNA (ssDNA)-functionalized single-wall carbon nanotubes (SWCNTs) exhibit exceptional optical sensitivity to catecholamines, including dopamine and norepinephrine—key signaling molecules that play vital roles in brain function. This unique capability positions SWCNTs as powerful tools for advancing our understanding of neurochemical processes involving dopaminergic and noradrenergic neurons. In this presentation, I will highlight how our lab has leveraged SWCNT nanosensors to push the boundaries of dopamine neuroscience. For studies in cultured neurons, we developed a composite nanofilm strategy that enabled us to visualize dopamine release with exceptional resolution, capturing single bouton activity with quantal sensitivity while monitoring thousands of release sites simultaneously in large imaging fields of view. By combining SWCNT-based activity imaging with immunofluorescence, electron microscopy, and cutting-edge molecular, cellular and genetic techniques, we have gained new insights into neurobiological properties of dopamine release sites in dopaminergic neurons that had heretofore been inaccessible with conventional methods of inquiry. Building on these advances, I will discuss recent progress in the development of in vivo-compatible dopamine nanosensors. These innovations have allowed us to monitor dopamine dynamics in awake and behaving mice, bridging the gap between molecular-scale imaging and real-time behavior analysis. Furthermore, I will discuss methodological developments that enabled the deployment of these nanosensors in vivo. Looking ahead, these SWCNT-enabled technological advancements hold potential for the study of neurochemical signaling, offering deeper insights into both normal brain function and the pathophysiology of disorders involving catecholamines. Future work aims to expand the applications of these nanosensors to other neural circuits and neuromodulators, ultimately advancing our ability to decode the brain’s chemical language.

We address the problem of inferring the number of independently blinking fluorescent light emitters, when only their combined intensity contributions can be observed. This problem occurs regularly in light microscopy of objects smaller than the diffraction limit, where one wishes to count the number of fluorescently labeled subunits. Our proposed solution directly models the photophysics of the system, as well as the blinking kinetics of the fluorescent emitters as a fully differentiable hidden Markov model, estimating a posterior distribution of the total number of emitters. We show that our model is more accurate and increases the range of countable subunits by a factor of 2 compared to current state-of-the-art methods. Furthermore, we demonstrate that our model can be used to investigate the effect of blinking kinetics on counting ability and therefore can inform optimal experimental conditions.

Many animals navigate using optic flow, detecting rotational image velocity differences between their eyes to adjust direction. Forward locomotion produces strong symmetric translational optic flow that can mask these differences, yet the brain efficiently extracts these binocular asymmetries for course control. In Drosophila melanogaster, monocular horizontal system neurons facilitate detection of binocular asymmetries and contribute to steering. To understand these functions, we reconstructed horizontal system cells' central network using electron microscopy datasets, revealing convergent visual inputs, a recurrent inhibitory middle layer and a divergent output layer projecting to the ventral nerve cord and deeper brain regions. Two-photon imaging, GABA receptor manipulations and modeling, showed that lateral disinhibition reduces the output's translational sensitivity while enhancing its rotational selectivity. Unilateral manipulations confirmed the role of interneurons and descending outputs in steering. These findings establish competitive disinhibition as a key circuit mechanism for detecting rotational motion during translation, supporting navigation in dynamic environments.

Preprint: https://doi.org/10.1101/2023.08.06.552150

We present a correlated light and electron microscopy (CLEM) dataset from a 7-day-old larval zebrafish, integrating confocal imaging of genetically labeled excitatory (vglut2a) and inhibitory (gad1b) neurons with nanometer-resolution serial section EM. The dataset spans the brain and anterior spinal cord, capturing >180,000 segmented soma, >40,000 molecularly annotated neurons, and 30 million synapses, most of which were classified as excitatory, inhibitory, or modulatory. To characterize the directional flow of activity across the brain, we leverage the synaptic and cell body annotations to compute region-wise input and output drive indices at single cell resolution. We illustrate the dataset’s utility by dissecting and validating circuits in three distinct systems: water flow direction encoding in the lateral line, recurrent excitation and contralateral inhibition in a hindbrain motion integrator, and functionally relevant targeted long-range projections from a tegmental excitatory nucleus, demonstrating that this resource enables rigorous hypothesis testing as well as exploratory-driven circuit analysis. The dataset is integrated into an open-access platform optimized to facilitate community reconstruction and discovery efforts throughout the larval zebrafish brain.

Preprint: https://www.biorxiv.org/content/early/2025/06/15/2025.06.10.658982

Artificial neural networks learn faster if they are initialized well. Good initializations can generate high-dimensional macroscopic dynamics with long timescales. It is not known if biological neural networks have similar properties. Here we show that the eigenvalue spectrum and dynamical properties of large-scale neural recordings in mice (two-photon and electrophysiology) are similar to those produced by linear dynamics governed by a random symmetric matrix that is critically normalized. An exception was hippocampal area CA1: population activity in this area resembled an efficient, uncorrelated neural code, which may be optimized for information storage capacity. Global emergent activity modes persisted in simulations with sparse, clustered or spatial connectivity. We hypothesize that the spontaneous neural activity reflects a critical initialization of whole-brain neural circuits that is optimized for learning time-dependent tasks.

The brain is a disproportionately large consumer of fuel, estimated to expend \~20% of the whole-body energy budget, and therefore it is critical to adequately control brain fuel expenditures while satisfying its on-demand needs for continued function. The brain is also metabolically vulnerable as the inability to adequately fuel cellular processes that support information transfer between cells leads to rapid neurological impairment. We show here that a genetic driver of early onset epileptic encephalopathy (EOEE), SLC13A5, a Na+/citrate cotransporter (NaCT), is critical for gating the activation of local presynaptic glycolysis. We show that SLC13A5 is in part localized to a presynaptic pool of membrane-bound organelles and acts to transiently clear axonal citrate during electrical activity, in turn activating phosphofructokinase 1. We show that loss of SLC13A5 or mistargeting to the plasma membrane results in suppressed glycolytic gating, activity dependent presynaptic bioenergetic deficits and synapse dysfunction.

Understanding biological systems requires observing features and processes across vast spatial and temporal scales, spanning nanometers to centimeters and milliseconds to days, often using multiple imaging modalities within complex native microenvironments. Yet, achieving this comprehensive view is challenging because microscopes optimized for specific tasks typically lack versatility due to inherent optical and sample handling trade-offs, and frequently suffer performance degradation from sample-induced optical aberrations in multicellular contexts. Here, we present MOSAIC, a reconfigurable microscope that integrates multiple advanced imaging techniques including light-sheet, label-free, super-resolution, and multi-photon, all equipped with adaptive optics. MOSAIC enables non-invasive imaging of subcellular dynamics in both cultured cells and live multicellular organisms, nanoscale mapping of molecular architectures across millimeter-scale expanded tissues, and structural/functional neural imaging within live mice. MOSAIC facilitates correlative studies across biological scales within the same specimen, providing an integrated platform for broad biological investigation.

Preprint: https://www.biorxiv.org/content/early/2025/06/13/2025.06.02.657494

The endoplasmic reticulum donates lipids through a tunnel-like protein to help lysosomes expand.

Microscopy drives biological discovery, yet high costs limit its access to resource-limited regions. We highlight examples of successful frugal microscopes that have overcome adoption barriers, offering a roadmap to expand affordable, quantitative imaging tools and foster impactful research in resource-limited settings.

Summary Solute carrier family 11 member 1 (SLC11A1) is critical for host resistance to diverse intracellular pathogens. During infection, SLC11A1 limits Salmonella’s access to iron, zinc, and magnesium, but only magnesium deprivation significantly impairs Salmonella replication. To understand the unexpected minor impact of iron, we determined Salmonella’s iron access in infected SLC11A1-deficient and normal mice. Using reporter strains and mass spectrometry of Salmonella purified from the spleen, we found that SLC11A1 caused growth-restricting iron deprivation in a subset of Salmonella. Volume electron microscopy revealed that another Salmonella subset circumvented iron restriction by targeting iron-rich endosomes in macrophages degrading red blood cells (erythrophagocytosis). These iron-replete bacteria dominated overall Salmonella growth, masking the effects of the other Salmonella subset’s iron deprivation. Thus, SLC11A1 effectively sequesters iron, but heterogeneous Salmonella populations partially bypass this nutritional immunity by targeting iron-rich tissue microenvironments.