Biology subjects

Podgorski, K.

Publications and source records attributed to Podgorski, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Dynamo: An open-source Python application for quantifying neuronal structural plasticity over time

Neurons exhibit tremendous structural plasticity during the growth of dendritic and axonal arbors in early brain circuit formation, followed by experience-driven structural plasticity throughout life. Advances in labeling and in vivo time-lapse imaging allow capture of dynamic structural changes within intact and awake animals, and fluorescent biosensors of neural activity offer opportunities to link structural and functional plasticity. However, the resulting large multi-dimensional data sets are challenging to quantify due to time-consuming tracking of minute structural changes throughout complex neuronal morphologies across time. Here, we present Dynamo: an open-source Python application that enables dynamic morphometrics, the quantitative analysis of morphological changes over time, by streamlining arbor reconstruction, registration of structures across time, and quantitative analyses of growth behavior. Dynamo yields rich characterization of neural structural changes necessary for determining how rapid growth events culminate into long-term patterning, linking structural and functional plasticity, and for identifying underlying molecular mechanisms.

neuroscience↗

bioRxiv2026

GIAnT: a Glutamate Imaging Analysis Toolbox

Recent advances in fluorescent indicators and optical microscopy now enable in vivo synaptic imaging of glutamate, which transmits the majority of signals between neurons in the brain. Extracting fluorescence signals from these recordings is complicated by the minuscule scale and dense clustering of synapses on dendrites, as well as brain motion in behaving animals. Here we present the Glutamate Imaging Analysis Toolbox (GIAnT), a set of automated tools for glutamate imaging data that corrects sample motion, identifies active synapses with super-resolution precision, and extracts synaptic fluorescence signals. Compared to methods designed for cellular imaging, GIAnT reduces motion artifacts, more accurately identifies active synapses, and improves extracted signal quality by reducing contamination from overlapping synapses. By pairing in vivo glutamate imaging with post hoc expansion microscopy, we find that >70% of the putative synapses extracted using GIAnT matched one-to-one with glutamatergic synapses onto the postsynaptic cell. Our results establish GIAnT as an automated and validated pipeline for processing synaptic glutamate imaging data at scale.

neuroscience↗

bioRxiv2026

Ultrasensitive voltage imaging reveals distinct electrical microdomains in neurons

For the brain to compute, electrical signals must propagate over the membranes of individual neurons, connecting synaptic inputs to synaptic outputs1. Complex neuronal morphologies coupled with the spatial organization of synaptic inputs and outputs enable diverse voltage transformations that underlie cell-type specific computations2,3. However, measuring these transformations in vivo has remained challenging, leaving a crucial gap in our mechanistic understanding of single neuron computation. Here, we develop ASAP7y, a genetically encoded voltage indicator with unprecedented subthreshold sensitivity and expanded excitation compatibility in both mice and flies. We leveraged ASAP7y combined with two-photon random-access microscopy to record sensory stimulus-evoked voltage dynamics with millisecond, subcellular, and subthreshold resolution along the neurites of individual neurons in Drosophila. We found remarkable heterogeneity in voltage propagation across cell-types, delineating a fundamental axis of electrical diversity. Leveraging a nanoscale EM reconstruction of the visual system4, we modeled the electrotonic properties of single neurons spanning 717 cell types, revealing how morphology shapes voltage transformations. Finally, we demonstrate that confined voltage propagation creates substrates for local computation, producing subcellular domains with distinct feature selectivity across multiple cell types. These results provide mechanistic insight into how critical single neuron computations arise and reveal parallel processing in single neurons.

neuroscience↗

bioRxiv2025

A sensitive orange fluorescent calcium ion indicator for imaging neural activity

Genetically encoded calcium indicators (GECIs) are vital tools for fluorescence-based visualization of neuronal activity with high spatial and temporal resolution. However, current highest-performance GECIs are predominantly green or red fluorescent, limiting multiplexing options and efficient excitation with fixed-wavelength femtosecond lasers operating at 1030 nm. Here, we introduce OCaMP (also known as O-GECO2), an orange fluorescent GECI engineered from O-GECO1 through targeted substitutions to improve calcium affinity while retaining the favorable photophysical properties of mOrange2. OCaMP exhibits improved two-photon cross-section, responsiveness, photostability, and calcium affinity relative to O-GECO1. In cultured neurons, zebrafish, and mouse cortex, OCaMP outperforms the red GECIs jRCaMP1a and jRGECO1a in sensitivity, kinetics, and signal-to-noise ratio. These properties establish OCaMP as a robust tool for high-fidelity neural imaging optimized for 1030 nm excitation and a compromise-free option within the spectral gap between existing green and red GECIs.

neuroscience↗

bioRxiv2025

Glutamate indicators with increased sensitivity and tailored deactivation rates

Identifying the input-output operations of neurons requires measurements of synaptic transmission simultaneously at many of a neurons thousands of inputs in the intact brain. To facilitate this goal, we engineered and screened 3365 variants of the fluorescent protein glutamate indicator iGluSnFR3 in neuron culture, and selected variants in the mouse visual cortex. Two variants have high sensitivity, fast activation (< 2 ms) and deactivation times tailored for recording large populations of synapses (iGluSnFR4s, 153 ms) or rapid dynamics (iGluSnFR4f, 26 ms). By imaging action-potential evoked signals on axons and visually-evoked signals on dendritic spines, we show that iGluSnFR4s/4f primarily detect local synaptic glutamate with single-vesicle sensitivity. The indicators detect a wide range of naturalistic synaptic transmission, including in the vibrissal cortex layer 4 and in hippocampal CA1 dendrites. iGluSnFR4 increases the sensitivity and scale (4s) or speed (4f) of tracking information flow in neural networks in vivo.

neuroscience↗

bioRxiv2024

A novel rhodopsin-based voltage indicator for simultaneous two-photon optical recording with GCaMP in vivo

Genetically encoded voltage indicators (GEVIs) allow optical recording of membrane potential from targeted cells in vivo. However, red GEVIs that are compatible with two-photon microscopy and that can be multiplexed in vivo with green reporters like GCaMP, are currently lacking. To address this gap, we explored diverse rhodopsin proteins as GEVIs and engineered a novel GEVI, 2Photron, based on a rhodopsin from the green algae Klebsormidium nitens. 2Photron, combined with two photon ultrafast local volume excitation (ULoVE), enabled multiplexed readout of spiking and subthreshold voltage simultaneously with GCaMP calcium signals in visual cortical neurons of awake, behaving mice. These recordings revealed the cell-specific relationship of spiking and subthreshold voltage dynamics with GCaMP responses, highlighting the challenges of extracting underlying spike trains from calcium imaging.

neuroscience↗

bioRxiv2023

A blue-shifted genetically encoded Ca2+ indicator with enhanced two-photon absorption

SignificanceGenetically encoded calcium ion (Ca2+) indicators (GECIs) are powerful tools for monitoring intracellular Ca2+ concentration changes in living cells and model organisms. In particular, GECIs have found particular utility for monitoring the transient increase of Ca2+ concentration that is associated with the neuronal action potential. However, the palette of highly optimized GECIs for imaging of neuronal activity remains relatively limited. Expanding the selection of available GECIs to include new colors and distinct photophysical properties could create new opportunities for in vitro and in vivo fluorescence imaging of neuronal activity. In particular, blue-shifted variants of GECIs are expected to have enhanced two-photon brightness, which would facilitate multiphoton microscopy. AimWe describe the development and applications of T-GECO1 - a high-performance blue-shifted GECI based on the Clavularia sp.-derived mTFP1. ApproachWe used protein engineering and extensive directed evolution to develop T-GECO1. We characterize the purified protein and assess its performance in vitro using one-photon excitation in cultured rat hippocampal neurons, in vivo using one-photon excitation fiber photometry in mice, and ex vivo using two-photon Ca2+ imaging in hippocampal slices. ResultsThe Ca2+-bound state of T-GECO1 has an excitation peak maximum of 468 nm, an emission peak maximum of 500 nm, an extinction coefficient of 49,300 M-1cm-1, a quantum yield of 0.83, and two-photon brightness approximately double that of EGFP. The Ca2+-dependent fluorescence increase is 15-fold and the apparent Kd for Ca2+ is 82 nM. With two-photon excitation conditions at 850 nm, T-GECO1 consistently enabled detection of action potentials with higher signal-to-noise (SNR) than a late generation GCaMP variant. ConclusionT-GECO1 is a high performance blue-shifted GECI that, under two-photon excitation conditions, provides advantages relative to late generation GCaMP variants.

neuroscience↗

bioRxiv2022

Improved genetically encoded fluorescent biosensors for monitoring of intra- and extracellular L-lactate

O_SCPLOWLC_SCPLOW-Lactate is increasingly appreciated as a key metabolite and signaling molecule in mammals. To enable investigations of both the inter- and intra-cellular dynamics of O_SCPLOWLC_SCPLOW-Lactate, we develop a second-generation green fluorescent extracellular O_SCPLOWLC_SCPLOW-Lactate biosensor, designated eLACCO2.1, and a red fluorescent intracellular O_SCPLOWLC_SCPLOW-Lactate biosensor, designated R-iLACCO1. Compared to the first-generation eLACCO1.1 ({Delta}F/F = 1.5 in cultured neurons), eLACCO2.1 exhibits better membrane localization and fluorescence response ({Delta}F/F = 8.1 in cultured neurons) with faster response kinetics to extracellular O_SCPLOWLC_SCPLOW-Lactate on the surface of live mammalian cells. R-iLACCO1 and its affinity variants exhibit large fluorescence responses to changes in O_SCPLOWLC_SCPLOW-Lactate concentration in vitro ({Delta}F/F = 15 to 22) and in live mammalian cells ({Delta}F/F = 5.5 to 11). We demonstrate that these biosensors enable cellular-resolution imaging of extracellular and intracellular O_SCPLOWLC_SCPLOW-Lactate in cultured mammalian cells.

molecular biology↗

bioRxiv2022

GESIAP: A Versatile Genetically Encoded Sensor-based Image Analysis Program

Intercellular communication mediated by a large number of neuromodulators diversifies physiological actions, yet neuromodulation remains poorly understood despite the recent upsurge of genetically encoded transmitter sensors. Here, we report the development of a versatile genetically encoded sensor-based image analysis program (GESIAP) that utilizes MATLAB-based algorithms to achieve high-throughput, high-resolution processing of sensor-based functional imaging data. GESIAP enables delineation of fundamental properties (e.g., transmitter spatial diffusion extent, quantal size, quantal content, release probability, pool size, and refilling rate at single release sites) of transmission mediated by various transmitters (i.e., monoamines, acetylcholine, neuropeptides, and glutamate) at various cell types (i.e., neurons, astrocytes, and other non-neuronal cells) of various animal species (i.e., mouse, rat, and human). Our analysis appraises a dozen of newly developed transmitter sensors, validates a conserved model of restricted non-volume neuromodulatory synaptic transmission, and accentuates a broad spectrum of presynaptic release properties that variegate neuromodulation.

neuroscience↗

bioRxiv2022

Activity-driven synaptic translocation of LGI1 controls excitatory neurotransmission

The fine control of synaptic function requires robust trans-synaptic molecular interactions. However, it remains poorly understood how the landscape of trans-synaptic bridges dynamically remodels to reflect functional states of the synapse. Here we developed novel optical tools to visualize in firing synapses the molecular behavior of a particular secreted trans-synaptic protein, LGI1, and its presynaptic receptor, ADAM23, and discovered that neuronal activity acutely rearranges the abundance of these proteins at the synaptic cleft. Surprisingly, LGI1 in synapses was not secreted, as described elsewhere, but exo- and endocytosed through its interaction with ADAM23. Activity-driven translocation of LGI1 facilitated the formation of trans-synaptic connections proportionally to the history of activity of the synapse, adjusting excitatory transmission to synaptic firing rates. Thus, our findings reveal that LGI1 abundance at the synaptic cleft can be acutely remodeled and serves as a critical point of activity-dependent control of synaptic function. Highlights- Neuronal activity translocates LGI1 and ADAM23 to the presynaptic surface - LGI1 and ADAM23 are not located in synaptic vesicles - Stable cleft localization of LGI1 depends on the history of synaptic activity - LGI1 abundance at the synaptic cleft controls glutamate release

neuroscience↗

bioRxiv2022

Glutamate indicators with improved activation kinetics and localization for imaging synaptic transmission

The fluorescent glutamate indicator iGluSnFR enables imaging of neurotransmission with genetic and molecular specificity. However, existing iGluSnFR variants exhibit saturating activation kinetics and are excluded from post-synaptic densities, limiting their ability to distinguish synaptic from extrasynaptic glutamate. Using a multi-assay screen in bacteria, soluble protein, and cultured neurons, we generated novel variants with improved kinetics and signal-to-noise ratios. We also developed surface display constructs that improve iGluSnFRs nanoscopic localization to post-synapses. The resulting indicator, iGluSnFR3, exhibits rapid non-saturating activation kinetics and reports synaptic glutamate release with improved linearity and increased specificity versus extrasynaptic signals in cultured neurons. In mouse visual cortex, imaging of iGluSnFR3 at individual boutons reported single electrophysiologically-observed action potentials with high specificity versus non-synaptic transients. In vibrissal sensory cortex Layer 4, we used iGluSnFR3 to characterize distinct patterns of touch-evoked feedforward input from thalamocortical boutons and both feedforward and recurrent input onto L4 cortical neuron dendritic spines.

neuroscience↗

bioRxiv2021

A sensitive and specific genetically encodable biosensor for potassium ions

Potassium ions (K+) play a critical role as an essential electrolyte in all biological systems. Here we report the crystal structure-guided optimization and directed evolution of an improved genetically encoded fluorescent K+ biosensor, GINKO2. GINKO2 is highly sensitive and specific for K+ and enables in vivo detection of K+ dynamics in multiple species.

bioengineering↗

bioRxiv2021

A genetically encoded fluorescent biosensor for extracellular L-lactate

To enable investigations of the emerging roles of cell-to-cell shuttling of L-lactate, we have developed an intensiometric green fluorescent genetically encoded biosensor for extracellular L-lactate. We demonstrate that this biosensor, designated eLACCO1.1, enables minimally invasive cellular resolution imaging of extracellular L-lactate in cultured mammalian cells and brain tissue.

molecular biology↗

bioRxiv2021

Comprehensive imaging of synaptic activity reveals dendritic growth rules that cluster inputs

The distribution of synapses across dendritic arbors determines their contribution to neural computations since nonlinear conductances amplify co-active clustered inputs. To determine whether, and how patterned synaptic topography arises during development we developed a random-access microscope capable of full-neuron calcium imaging of activity and structural plasticity of developing neurons in awake Xenopus tadpoles. By imaging growing brain neurons in response to plasticity-inducing visual training, we show coordinated growth and synaptogenesis specific to each neurons spike tuning. High evoked activity in neurons tuned to the trained stimulus induced pruning of non-driven inputs across the dendritic arbor as these neurons strengthened their responses to this stimulus. In stark contrast, initially unresponsive neurons that shifted their spike tuning toward the trained stimulus exhibited localized growth and new responsive synapses near existing active inputs. These information-driven growth rules promote clustering of synapses tuned to a developing neurons emerging receptive field. One-Sentence SummarySensory input directs brain neuronal growth and connectivity promoting clustering of synaptic inputs tuned to a neurons encoding properties.

neuroscience↗

bioRxiv2020

Far-red fluorescent genetically encoded calcium ion indicators

Genetically encoded calcium ion (Ca2+) indicators (GECIs) are widely-used molecular tools for functional imaging of Ca2+ dynamics and neuronal activities on a single cell level. Here we report the design and development of two new far-red fluorescent GECIs, FR-GECO1a and FR-GECO1c, based on the monomeric far-red fluorescent protein mKelly. We characterized these far-red GECIs as purified proteins and assessed their performance when expressed in cultured neurons. FR-GECOs have excitation and emission maxima at ~ 596 nm and ~ 644 nm, respectively, display large responses to Ca2+ ({Delta}F/F0 = 6 for FR-GECO1a, 18 for FR-GECO1c), and are bright under both one-photon and two-photon illumination. FR-GECOs also have high affinities (apparent Kd = 29 nM for FR-GECO1a, 83 nM for FR-GECO1c) for Ca2+, and they enable sensitive and fast detection of single action potentials in neurons.

neuroscience↗

bioRxiv2020

A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

Here we design and optimize a genetically encoded fluorescent indicator, iAChSnFR, for the ubiquitous neurotransmitter acetylcholine, based on a bacterial periplasmic binding protein. iAChSnFR shows large fluorescence changes, rapid rise and decay kinetics, and insensitivity to most cholinergic drugs. iAChSnFR revealed large transients in a variety of slice and in vivo preparations in mouse, fish, fly and worm. iAChSnFR will be useful for the study of acetylcholine in all animals.

neuroscience↗

bioRxiv2020

A bright and high-performance genetically encoded Ca2+ indicator based on mNeonGreen fluorescent protein

Genetically encodable calcium ion (Ca2+) indicators (GECIs) based on green fluorescent proteins (GFP) are powerful tools for imaging of cell signaling and neural activity in model organisms. Following almost two decades of steady improvements in the Aequorea victoria GFP (avGFP)-based GCaMP series of GECIs, the performance of the most recent generation (i.e., GCaMP7) may have reached its practical limit due to the inherent properties of GFP. In an effort to sustain the steady progression towards ever-improved GECIs, we undertook the development of a new GECI based on the bright monomeric GFP, mNeonGreen (mNG). The resulting indicator, mNG-GECO1, is 60% brighter than GCaMP6s in vitro and provides comparable performance as demonstrated by imaging Ca2+ dynamics in cultured cells, primary neurons, and in vivo in larval zebrafish. These results suggest that mNG-GECO1 is a promising next-generation GECI that could inherit the mantle of GCaMP and allow the steady improvement of GECIs to continue for generations to come.

molecular biology↗

bioRxiv2020

VolPy: automated and scalable analysis pipelines for voltage imaging datasets

Voltage imaging enables monitoring neural activity at sub-millisecond and sub-compartment scale, and therefore opens the path to studying sub-threshold activity, synchrony, and network dynamics with unprecedented spatio-temporal resolution. However, high data rates (>800MB/s) and low signal-to-noise ratios have created a severe bottleneck for analysis of such datasets. Here we present VolPy, the first turn-key, automated and scalable pipeline to pre-process voltage imaging datasets. VolPy features fast motion correction, memory mapping, segmentation, and spike inference, all built on a highly parallelized and computationally efficient framework that optimizes memory and speed. Given the lack of single cell voltage imaging ground truth examples, we introduce a corpus of 24 manually annotated datasets from different preparations and voltage indicators. We benchmark VolPy against this corpus and electrophysiology recordings, demonstrating excellent performance in neuron localization, spike extraction, and scalability.

neuroscience↗