Biology subjects

Rudin, M.

Publications and source records attributed to Rudin, M..

13 recordsLinked to original sources

bioRxiv2026

MR-μScope: a multi-scale and simultaneous MRI-miniaturized microscopy system for elucidating neurovascular coupling

Blood Oxygen Level Dependent functional MRI (BOLD-fMRI) revolutionized non-invasive brain mapping, yet the physiological origins of its signal, linking microscopic neurovascular activity to macroscopic hemodynamics, remain elusive. To bridge this gap, we developed MR-Scope: a simultaneous and multimodal platform that integrates preclinic high-field MRI (9.4T) and miniaturized fluorescence microscopy (Miniscope). Our system contains an MR-compatible Miniscope with electromagnetic shielding, a customized radiofrequency coil with a central optical window, and an adjustable animal cradle, enabling artifact-free acquisition of whole-brain fMRI alongside microscopic vascular dynamics. Phantom validation confirmed negligible cross-modal interference (fMRI SNR [≥] 15 dB; optical SNR [≥] 26 dB). MR-Scope captured stimulus-evoked microvascular dilation and blood flow velocity changes in the somatosensory cortex concurrent with BOLD signals, revealing vessel-size-dependent neurovascular coupling. MR-Scope provides an effective solution for deciphering multi-scale neurovascular interactions and offers unique potential for advancing research into brain function and disease mechanisms involving vascular pathology.

bioengineering↗

bioRxiv2024

Delineating redox cooperativity in water-soluble and membrane multiheme cytochromes through protein design

Nature has evolved diverse electron transport proteins and multiprotein assemblies essential to the generation and transduction of biological energy. However, substantially modifying or adapting these proteins for user-defined applications or to gain fundamental mechanistic insight can be hindered by their inherent complexity. De novo protein design offers an attractive route to stripping away this confounding complexity, enabling us to probe the fundamental workings of these bioenergetic proteins and systems, while providing robust, modular platforms for constructing completely artificial electron-conducting circuitry. Here, we use a set of de novo designed mono-heme and di-heme soluble and membrane proteins to unpick the contributions of electrostatic micro-environments and dielectric properties of the surrounding protein medium on the inter-heme redox cooperativity that we have previously reported. Experimentally, we find that the two heme sites in both the water-soluble and membrane constructs have broadly equivalent redox potentials in isolation, in agreement with Poisson-Boltzmann Continuum Electrostatics calculations. BioDC, a Python program for the estimation of electron transfer energetics and kinetics within multiheme cytochromes, also predicts equivalent heme sites, and reports that burial within the low dielectric environment of the membrane strengthens heme-heme electrostatic coupling. We conclude that redox cooperativity in our diheme cytochromes is largely driven by heme electrostatic coupling and confirm that this effect is greatly strengthened by burial in the membrane. These results demonstrate that while our de novo proteins present minimalist, new-to-nature constructs, they enable the dissection and microscopic examination of processes fundamental to the function of vital, yet complex, bioenergetic assemblies.

biochemistry↗

bioRxiv2022

Neuromodulation of striatal D1 cells shapes BOLD fluctuations in anatomically connected thalamic and cortical regions

Understanding how the brains macroscale dynamics are shaped by underlying microscale mechanisms is a key problem in neuroscience. In animal models, we can now investigate this relationship in unprecedented detail by directly manipulating cellular-level properties while measuring the whole-brain response using resting-state fMRI. Here we focused on understanding how blood-oxygen-level-dependent (BOLD) dynamics, measured within a structurally well-defined striato-thalamo-cortical circuit, are shaped by chemogenetically exciting or inhibiting D1 medium spiny neurons (MSNs) of the right dorsomedial striatum (CPdm). We characterize changes in both the BOLD dynamics of individual cortical and subcortical brain areas, and patterns of inter-regional coupling (functional connectivity) between pairs of areas. Using a classification approach based on a large and diverse set of time-series properties, we found that CPdm neuromodulation alters BOLD dynamics within thalamic subregions that project back to dorsomedial striatum. In the cortex, the strongest changes in local dynamics were observed in unimodal regions, i.e., regions that process information from a single sensory modality, while changes in the local dynamics weakened along a putative cortical hierarchical gradient towards transmodal regions. In contrast, a decrease in functional connectivity was observed only for cortico-striatal connections after D1 excitation. Our results provide a comprehensive understanding of how targeted cellular-level manipulations affect local BOLD dynamics at the macroscale, including the role of a circuits structural characteristics and hierarchical cortical level in shaping those dynamics. These findings contribute to ongoing attempts to understand the influence of structure-function relationships in shaping inter-regional communication at subcortical and cortical levels.

neuroscience↗

bioRxiv2021

Non-invasive visualization of amyloid-beta deposits in Alzheimer amyloidosis mice using magnetic resonance imaging and fluorescence molecular tomography

Abnormal cerebral accumulation of amyloid-beta peptide (A{beta}) is a major hallmark of Alzheimers disease. Non-invasive monitoring of A{beta} deposits enables assessing the disease burden in patients and animal models mimicking aspects of the human disease as well as evaluating the efficacy of A{beta}-modulating therapies. Previous in vivo assessments of plaque load in mouse models of cerebral amyloidosis have been predominantly based on two-dimensional diffuse fluorescence reflectance imaging (2D-FRI) and two-photon microscopy (2PM) using A{beta}-specific imaging agents. However, 2D-FRI lacks depth resolution, whereas 2PM is restricted by the limited field of view preventing coverage of large brain regions. Here, we utilized a magnetic resonance imaging (MRI) and fluorescence molecular tomography (FMT) pipeline with the curcumin derivative fluorescent probe CRANAD-2 to achieve full 3D brain coverage for detecting A{beta} accumulation in the arcA{beta} mouse model of cerebral amyloidosis. A homebuilt FMT system was used for data acquisition in combination with a customized software platform enabling the integration of anatomical information derived from MRI as prior information for FMT image reconstruction. The results obtained from the FMT-MRI study were compared to data obtained from conventional 2D-FRI recorded under similar physiological conditions. The two methods yielded comparable time courses of the fluorescence intensity following intravenous injection of CRANAD-2 in a region of interest comprising the mouse brain. The depth resolution inherent to FMT allowed separation of signal contributions from the scalp and different brain regions, indicating preferential accumulation of the fluorescent tracer in the cerebral cortex, a region characterized by significant plaque deposition in arc A{beta} mice. In conclusion, we have demonstrated the feasibility of visualizing A{beta} deposition in 3D using a multimodal FMT-MRI method. This hybrid imaging method provides complementary anatomical, physiological and molecular information, thereby enabling the detailed characterization of the disease status in mouse models of cerebral amyloidosis, which is also important for monitoring the efficacy of putative treatments targeting A{beta}.

neuroscience↗

bioRxiv2020

Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes

Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modelled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches.

neuroscience↗

bioRxiv2020

Whole-Brain Longitudinal Profiling of Serotonergic Reuptake Inhibition

The serotonergic system is widely implicated in affect regulation, and a common target for psychopharmacological interventions. Selective Serotonin Reuptake Inhibitors (SSRIs) are the foremost drug class for treating depression, as well as anxiety, phobia and other affective disorders. However, the functional mechanisms determining SSRI efficacy remain elusive, hindering the targeted further development of serotonergic system interventions. Assays for longitudinal whole-brain interrogation of the serotonergic system are unavailable, yet such techniques are essential for identifying differential intervention effects across projection areas. We present a novel longitudinal opto-fMRI assay suitable for imaging longitudinal drug treatment effects on the mouse serotonergic system -- within-subject and with sub-millimetre spatial resolution. We apply this assay to a longitudinal fluoxetine treatment, and document reliable segmentation of brain-wide treatment effects, including identification of a brainstem cluster with a highly significant longitudinal trajectory, constituting a novel neurophenotype for psychopharmacological interventions. We differentiate serotonergic neuron activation from projection area activation, and offer brain-wide fMRI evidence for the prominent autoinhibition down-regulation theory of SSRI effects. Further, we show that given the sensitivity of the assay, SSRI treatment produces no persistent effects after treatment cessation in healthy subjects.

neuroscience↗

bioRxiv2020

A Whole-Brain Map and Assay Parameter Analysis of Mouse VTA Dopaminergic Activation

Ascending dopaminergic projections from neurons located in the Ventral Tegmental Area (VTA) are key to the etiology, dysfunction, and control of motivation, learning, and addiction. Due to evolutionary conservation of this nucleus and the extensive use of mice as disease models, establishing an assay for VTA dopaminergic signalling in the mouse brain is crucial for the translational investigation of motivational control as well as of neuronal function phenotypes for diseases and interventions. In this article we use optogenetic stimulation directed at VTA dopaminergic neurons in combination with functional Magnetic Resonance Imaging (fMRI), a method widely used in human deep brain imaging. We present a comprehensive assay producing the first whole-brain opto-fMRI map of dopaminergic activation in the mouse, and show that VTA dopaminergic system function is consistent with its structural VTA projections, diverging only in a few key aspects. While the activation map predominantly highlights target areas according to their relative projection densities (e.g. strong activation of the nucleus accumbens and low activation of the hippocampus), it also includes areas for which a structural connection is not well established (such as the dorsomedial striatum). We further detail the variability of the assay with regard to multiple experimental parameters, including stimulation protocol and implant position, and provide evidence-based recommendations for assay reuse, publishing both reference results and a reference analysis workflow implementation.

neuroscience↗

bioRxiv2020

Whole brain optoacoustic tomography reveals strain-specific regional beta-amyloid densities in Alzheimer`s disease amyloidosis models

Deposition of beta-amyloid (A{beta}) deposits is one major histopathological hallmark of Alzheimers disease (AD). Here, we introduce volumetric multi-spectral optoacoustic tomography (vMSOT), which covers 10x10x10 mm3 field-of-view, capable of 3D whole mouse brain imaging. We show for the first time the optoacoustic properties of oxazine-derivative AOI987 probe, which binds to A{beta}, and the application of vMSOT for the quantification of brain-wide A{beta} deposition. Administration of AOI987 to two common transgenic mouse strains of AD amyloidosis led to a retention of the probe in A{beta}-laden brain regions. Co-registered of vMSOT data to a brain atlas revealed strain-specific pattern of AOI987 uptake. A comparison with ex vivo light-sheet microscopy in cleared mouse brains showed a good correspondence in A{beta} distribution. Lastly, we demonstrate the specificity of the AOI987 probe by immunohistochemistry. vMSOT with AOI987 facilitates preclinical brain region-specific studies of A{beta} spread and accumulation, and the monitoring of putative treatments targeting A{beta}.

neuroscience↗

bioRxiv2019

Psilocybin exerts distinct effects on resting state networks associated with serotonin and dopamine in mice

Hallucinogenic agents have been proposed as potent antidepressants; this includes the serotonin (5-HT) receptor 2A agonist psilocybin. In human subjects, psilocybin alters functional connectivity (FC) within the default-mode network (DMN), a constellation of inter-connected regions that is involved in self-reference and displays altered FC in depressive disorders. In this study we investigated the effects of psilocybin on FC in the analogue of the DMN in mouse, with a view to establishing an experimental animal model to investigate underlying mechanisms. Psilocybin effects were investigated in lightly-anaesthetized mice using resting-state fMRI. Dual-regression analysis identified reduced FC within the ventral striatum in psilocybin-relative to vehicle-treated mice. Refinement of the analysis using spatial references derived from both gene expression maps and viral tracer projection fields revealed two distinct effects of psilocybin: it increased FC between 5-HT-associated networks and elements of the murine DMN, thalamus, and midbrain; it decreased FC within dopamine (DA)-associated striatal networks. These results suggest that interaction between 5-HT- and DA-regulated neural networks contributes to the neural and therefore psychological effects of psilocybin. Furthermore, they highlight how information on molecular expression patterns and structural connectivity can assist in the interpretation of pharmaco-fMRI findings.

neuroscience↗

bioRxiv2019

An Automated Open-Source Workflow for Standards-Compliant Integration of Small Animal Magnetic Resonance Imaging Data

Large-scale research integration is contingent on seamless access to data in standardized formats. Standards enable researchers to understand external experiment structures, pool results, and apply homogeneous preprocessing and analysis workflows. Particularly, they facilitate these features without the need for numerous potentially confounding compatibility add-ons. In small animal magnetic resonance imaging, an overwhelming proportion of data is acquired via the ParaVision software of the Bruker Corporation. The original data structure is predominantly transparent, but fundamentally incompatible with modern pipelines. Additionally, it sources metadata from free-field operator input, which diverges strongly between laboratories and researchers. In this article we present an open-source workflow which automatically converts and reposits data from the ParaVision structure into the widely supported and openly documented Brain Imaging Data Structure (BIDS). Complementing this workflow we also present operator guidelines for appropriate ParaVision data input, and a programmatic walk-through detailing how preexisting scans with uninterpretable metadata records can easily be made compliant after the acquisition.

neuroscience↗

bioRxiv2019

An Optimized Registration Workflow and Standard Geometric Space for Small Animal Brain Imaging

The reliability of scientific results critically depends on reproducible and transparent data processing. Cross-subject and cross-study comparability of imaging data in general, and magnetic resonance imaging (MRI) data in particular, is contingent on the quality of registration to a standard reference space. In small animal MRI this is not adequately provided by currently used processing workflows, which utilize high-level scripts optimized for human data, and adapt animal data to fit the scripts, rather than vice-versa. In this fully reproducible article we showcase a generic workflow optimized for the mouse brain, alongside a standard reference space suited to harmonize data between analysis and operation. We introduce four separate metrics for automated quality control (QC), and a visualization method to aid operator inspection. Benchmarking this workflow against common legacy practices reveals that it performs more consistently, better preserves variance across subjects while minimizing variance across sessions, and improves both volume and smoothness conservation RMSE approximately 2-fold. We propose this open source workflow and the QC metrics as a new standard for small animal MRI registration, ensuring workflow robustness, data comparability, and region assignment validity, all of which are indispensable prerequisites for the comparability of scientific results across experiments and centers.

neuroscience↗

bioRxiv2019

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories world-wide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a murine default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

neuroscience↗

bioRxiv2018

Cortical excitation:inhibition imbalance causes network specific functional hypoconnectivity: a DREADD-fMRI study

Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured withfunctional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here we applied fMRI while using chemogenetics to increase the excitation-to-inhibition ratio (E:I) within cortical microcircuits of the mouse brain, thereby mimicking a putative mechanism of neurodevelopmental disorders including autism. Increased E:I caused a significant reduction of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knock-out mice, a model for autism with well-documented loss of Parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.

neuroscience↗