Biology subjects

Kramer, R.

Publications and source records attributed to Kramer, R..

12 recordsLinked to original sources

bioRxiv2026

Tension TRAAKer: a chemigenetic fluorescent membrane tension reporter

Mechanical force transduction is essential to survival, underlying biological processes as fundamental as morphogenesis, somatosensation, audition, and interoception; and driving pathologies as diverse as hypertension and cancer metastasis. Exogenous forces are translated to intracellular signals through transient changes in membrane tension which are currently not possible to directly monitor in situ. To remedy this, we have designed and validated Tension TRAAKer, a chemigenetic fluorescent membrane tension reporter for the visualization of tension induction, propagation, and dissipation in living cells. Tension TRAAKer is derived from inserting a tension-sensitive nonconductive variant of the mechanosensitive potassium ion channel TRAAK into a self-labelling HaloTag. Increasing membrane tensions effect conformational changes in the TRAAK channel that are optically monitored by a HaloTag-conjugated fluorogenic (environment-sensitive) dye. EGFP incorporation C-terminal to the HaloTag enables unambiguous tension reporting in mobile membranes via dual-color ratiometric imaging that controls for variations in sensor density. Tension TRAAKer reports membrane tension changes rapidly, reversibly, and with spatiotemporal precision--its fluorescence scaling to both stimulus magnitude and area, with consistent effect sizes observed between diverse cell types. It better distinguishes among elevated membrane tensions than do available indirect chemical reporters, with the additional advantage of being readily genetically targetable. We thus expect Tension TRAAKer to be a powerful tool for the study of membrane tension across biological systems and disease states.

molecular biology↗

bioRxiv2025

An inherited mtDNA mutation remodels inflammatory cytokine responses in macrophages and in vivo

Impaired mitochondrial bioenergetics in macrophages can drive hyperinflammatory cytokine responses1-6, but whether this may also be caused by inherited mtDNA mutations is unknown. Here, we address this question using a multi-omic approach that integrates super-resolution imaging and metabolic analyses to profile macrophages from a mouse model of mitochondrial disease arising from a heteroplasmic mutation (m.5019A>G) in the mitochondrial tRNA for alanine7. These m.5019A>G macrophages exhibit defects in respiratory chain complexes and oxidative phosphorylation (OxPhos) due to decreased intra-mitochondrial translation. To adapt to this metabolic stress, mitochondrial fusion, reductive glutamine metabolism, and aerobic glycolysis are all increased. Upon inflammatory activation, type I interferon (IFN-I) release is enhanced, while the production of pro-inflammatory cytokines and oxylipins are restrained in m.5019A>G macrophages. Finally, an in vivo endotoxemia model using m.5019A>G mice reveal elevated IFN-I levels and sickness behaviour. In conclusion, our study identifies an unexpected imbalance in innate immune signalling in response to a pathogenic mtDNA mutation, with important implications for the progression of pathology in patients with mtDNA diseases8.

immunology↗

bioRxiv2024

A toolbox for ablating excitatory and inhibitory synapses

Recombinant optogenetic and chemogenetic proteins are potent tools for manipulating neuronal activity and controlling neural circuit function. However, there are few analogous tools for manipulating the structure of neural circuits. Here, we introduce three rationally designed genetically encoded tools that use E3 ligase-dependent mechanisms to trigger the degradation of synaptic scaffolding proteins, leading to functional ablation of synapses. First, we developed a constitutive excitatory synapse ablator, PFE3, analogous to the inhibitory synapse ablator GFE3. PFE3 targets the RING domain of the E3 ligase Mdm2 and the proteasome-interacting region of Protocadherin 10 to the scaffolding protein PSD-95, leading to efficient ablation of excitatory synapses. In addition, we developed a light-inducible version of GFE3, paGFE3, using a novel photoactivatable complex based on the photocleavable protein PhoCl2c. paGFE3 degrades Gephyrin and ablates inhibitory synapses in response to 400 nm light. Finally, we developed a chemically inducible version of GFE3, chGFE3, which degrades inhibitory synapses when combined with the bio-orthogonal dimerizer HaloTag ligand-trimethoprim. Each tool is specific, reversible, and capable of breaking neural circuits at precise locations.

neuroscience↗

bioRxiv2023

Retinoic acid-dependent loss of synaptic output from bipolar cells impairs visual information processing in inherited retinal degeneration.

In retinitis pigmentosa (RP), rod and cone photoreceptors degenerate, depriving downstream neurons of light-sensitive input, leading to vision impairment or blindness. Although downstream neurons survive, some undergo morphological and physiological remodeling. Bipolar cells (BCs) link photoreceptors, which sense light, to retinal ganglion cells (RGCs), which send information to the brain. While photoreceptor loss disrupts input synapses to BCs, whether BC output synapses remodel has remained unknown. Here we report that synaptic output from BCs plummets in RP mouse models of both sexes owing to loss of voltage-gated Ca2+ channels. Remodeling reduces the reliability of synaptic output to repeated optogenetic stimuli, causing RGC firing to fail at high stimulus frequencies. Fortunately, functional remodeling of BCs can be reversed by inhibiting the retinoic acid receptor (RAR). RAR inhibitors targeted to BCs present a new therapeutic opportunity for mitigating detrimental effects of remodeling on signals initiated either by surviving photoreceptors or by vision-restoring tools. Significance StatementPhotoreceptor degenerative disorders such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD) lead to vision impairment or blindness. Vision mediated by surviving photoreceptors or artificial vision restoration technologies, rely on bipolar cells retaining normal function despite photoreceptor death. We find that in two animal models of RP, synaptic transmission from both rod and cone bipolar cells is severely impaired owing to diminished voltage-gated calcium current, preventing postsynaptic amacrine cells and retinal ganglion cells from properly receiving and encoding visual information. We find that an inhibitor of the retinoic acid receptor restores both the calcium current and synaptic release from bipolar cells. These discoveries about bipolar cells reveal a new functional deficit in blindness and a potential therapeutically important solution.

neuroscience↗

bioRxiv2022

Retinal microvascular and neuronal pathologies probed in vivo by adaptive optical two-photon fluorescence microscopy

The retina, behind the transparent optics of the eye, is the only neural tissue whose physiology and pathology can be non-invasively probed by optical microscopy. The aberrations intrinsic to the mouse eye, however, prevent high-resolution investigation of retinal structure and function in vivo. Optimizing the design of a two-photon fluorescence microscope (2PFM) and sample preparation procedure, we found that adaptive optics (AO), by measuring and correcting ocular aberrations, is essential for resolving synapses and achieving three-dimensional cellular resolution in the mouse retina in vivo. Applying AO-2PFM to longitudinal retinal imaging in transgenic models of retinal pathology, we characterized microvascular lesions and observed microglial migration in a proliferative vascular retinopathy model, and found Lidocaine to effectively suppress retinal ganglion cell hyperactivity in a retinal degeneration model. Tracking structural and functional changes at high resolution longitudinally, AO-2PFM enables microscopic investigations of retinal pathology and pharmacology for disease diagnosis and treatment in vivo.

neuroscience↗

bioRxiv2021

Cellular selectivity of STING stimulation determines priming of tumor-specific T cell responses

T cells that recognize tumor antigens are crucial for anti-tumor immune responses. Induction of anti-tumor T cells in immunogenic tumors depends on STING, the intracellular innate immune receptor for cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) and related cyclic dinucleotides (CDNs). However, the optimal way to leverage STING activation in non-immunogenic tumors is still unclear. Here, we show that cGAMP delivery by intra-tumoral injection of virus-like particles (cGAMP-VLP) leads to differentiation of tumor-specific T cells, decrease in tumor regulatory T cells (Tregs) and anti-tumoral responses that synergize with PD1 blockade. By contrast, intra-tumoral injection of synthetic CDN leads to tumor necrosis and systemic T cell activation but no differentiation of tumor-specific T cells, and a demise of immune cells in injected tumors. Analyses of cytokine responses and genetic models revealed that cGAMP-VLP preferentially targets STING in dendritic cells at a 1000-fold less dose than synthetic CDN. Sub-cutaneous administration of cGAMP-VLP showed synergy when combined with a tumor Treg-depleting antibody to elicit systemic tumor-specific T cells, leading to complete and lasting tumor eradication. These finding show that cell targeting of STING stimulation shapes the anti-tumor T cell response and reveal a therapeutic strategy with T cell modulators.

immunology↗

bioRxiv2021

A Thermostable, Flexible RNA Vaccine Delivery Platform for Pandemic Response

Current RNA vaccines against SARS-CoV-2 are limited by instability of both the RNA and the lipid nanoparticle delivery system, requiring storage at -20{degrees}C or -70{degrees}C and compromising universally accessible vaccine distribution. This study demonstrates the thermostability and adaptability of a nanostructured lipid carrier (NLC) RNA vaccine delivery system for use in pandemic preparedness and pandemic response. Liquid NLC is stable at refrigerated temperatures for [≥] 1 year, enabling stockpiling and rapid deployment by point-of-care mixing with any vaccine RNA. Alternatively, NLC complexed with RNA may be readily lyophilized and stored at room temperature for [≥] 8 months or refrigerated temperature for [≥] 21 months. This thermostable RNA vaccine platform could significantly improve distribution of current and future pandemic response vaccines, particularly in low-resource settings. One Sentence SummaryAn RNA vaccine delivery system stable at room temperature for 8+ months and refrigerated for 21+ months.

bioengineering↗

bioRxiv2019

SISUA: SemI-SUpervised generative Autoencoder for single cell data

Single-cell transcriptomics offers a tool to study the diversity of cell phenotypes through snapshots of the abundance of mRNA in individual cells. Often there is additional information available besides the single cell gene expression counts, such as bulk transcriptome data from the same tissue, or quantification of surface protein levels from the same cells. In this study, we propose models based on the Bayesian generative approach, where protein quantification available as CITE-seq counts from the same cells are used to constrain the learning process, thus forming a semi-supervised model. The generative model is based on the deep variational autoencoder (VAE) neural network architecture.

bioinformatics↗

bioRxiv2019

Deep transcriptome sequencing of subgenual anterior cingulate cortex reveals disorder-specific expression changes in major psychiatric disorders

How do differences in onset, symptoms, and treatment response arise between various mental illnesses despite substantial overlap of genetic risk factors? To address this question, we carried out deep RNA sequencing of human postmortem subgenual anterior cingulate cortex, a key component of limbic circuits linked to mental illness. Samples were obtained from 200 individuals diagnosed with bipolar disorder, schizophrenia, or major depression, and controls. Differential expression analysis in cases versus controls detected modest differences that were similar across disorders, although transcript-level differences were more pronounced. Case-case comparisons revealed greater expression differences between disorders, including many genes and transcripts that were expressed in opposite directions in each diagnostic group, compared to controls. Relative transcript abundances were associated with common genetic variants that accounted for disproportionate fractions of diagnosis-specific heritability. Inherited genetic risk factors shape the brain transcriptome and contribute to diagnostic differences between broad classes of mental illness.

genomics↗

bioRxiv2018

BDQC: a general-purpose analytics tool for domain-blind validation of Big Data

Translational biomedical research is generating exponentially more data: thousands of whole-genome sequences (WGS) are now available; brain data are doubling every two years. Analyses of Big Data, including imaging, genomic, phenotypic, and clinical data, present qualitatively new challenges as well as opportunities. Among the challenges is a proliferation in ways analyses can fail, due largely to the increasing length and complexity of processing pipelines. Anomalies in input data, runtime resource exhaustion or node failure in a distributed computation can all cause pipeline hiccups that are not necessarily obvious in the output. Flaws that can taint results may persist undetected in complex pipelines, a danger amplified by the fact that research is often concurrent with the development of the software on which it depends. On the positive side, the huge sample sizes increase statistical power, which in turn can shed new insight and motivate innovative analytic approaches. We have developed a framework for Big Data Quality Control (BDQC) including an extensible set of heuristic and statistical analyses that identify deviations in data without regard to its meaning (domain-blind analyses). BDQC takes advantage of large sample sizes to classify the samples, estimate distributions and identify outliers. Such outliers may be symptoms of technology failure (e.g., truncated output of one step of a pipeline for a single genome) or may reveal unsuspected \" signal\" in the data (e.g., evidence of aneuploidy in a genome). We have applied the framework to validate real-world WGS analysis pipelines. BDQC successfully identified data outliers representing various failure classes, including genome analyses missing a whole chromosome or part thereof, hidden among thousands of intermediary output files. These failures could then be resolved by reanalyzing the affected samples. BDQC both identified hidden flaws as well as yielded new insights into the data. BDQC is designed to complement quality software development practices. There are multiple benefits from the application of BDQC at all pipeline stages. By verifying input correctness, it can help avoid expensive computations on flawed data. Analysis of intermediary and final results facilitates recovery from aberrant termination of processes. All these computationally inexpensive verifications reduce cryptic analytical artifacts that could seriously preclude clinical-grade genome interpretation. BDQC is available at https://github.com/ini-bdds/bdqc.

bioinformatics↗

bioRxiv2017

Gene expression imputation across multiple brain regions reveals schizophrenia risk throughout development.

Transcriptomic imputation approaches offer an opportunity to test associations between disease and gene expression in otherwise inaccessible tissues, such as brain, by combining eQTL reference panels with large-scale genotype data. These genic associations could elucidate signals in complex GWAS loci and may disentangle the role of different tissues in disease development. Here, we use the largest eQTL reference panel for the dorso-lateral pre-frontal cortex (DLPFC), collected by the CommonMind Consortium, to create a set of gene expression predictors and demonstrate their utility. We applied these predictors to 40,299 schizophrenia cases and 65,264 matched controls, constituting the largest transcriptomic imputation study of schizophrenia to date. We also computed predicted gene expression levels for 12 additional brain regions, using publicly available predictor models from GTEx. We identified 413 genic associations across 13 brain regions. Stepwise conditioning across the genes and tissues identified 71 associated genes (67 outside the MHC), with the majority of associations found in the DLPFC, and of which 14/67 genes did not fall within previously genome-wide significant loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple pathways associated with porphyric disorders. We investigated developmental expression patterns for all 67 non-MHC associated genes using BRAINSPAN, and identified groups of genes expressed specifically pre-natally or post-natally.

genetics↗

bioRxiv2017

Transcriptomic Imputation of Bipolar Disorder and Bipolar subtypes reveals 29 novel associated genes

Bipolar disorder is a complex neuropsychiatric disorder presenting with episodic mood disturbances. In this study we use a transcriptomic imputation approach to identify novel genes and pathways associated with bipolar disorder, as well as three diagnostically and genetically distinct subtypes. Transcriptomic imputation approaches leverage well-curated and publicly available eQTL reference panels to create gene-expression prediction models, which may then be applied to \"impute\" genetically regulated gene expression (GREX) in large GWAS datasets. By testing for association between phenotype and GREX, rather than genotype, we hope to identify more biologically interpretable associations, and thus elucidate more of the genetic architecture of bipolar disorder.\n\nWe applied GREX prediction models for 13 brain regions (derived from CommonMind Consortium and GTEx eQTL reference panels) to 21,488 bipolar cases and 54,303 matched controls, constituting the largest transcriptomic imputation study of bipolar disorder (BPD) to date. Additionally, we analyzed three specific BPD subtypes, including 14,938 individuals with subtype 1 (BD-I), 3,543 individuals with subtype 2 (BD-II), and 1,500 individuals with schizoaffective subtype (SAB).\n\nWe identified 125 gene-tissue associations with BPD, of which 53 represent independent associations after FINEMAP analysis. 29/53 associations were novel; i.e., did not lie within 1Mb of a locus identified in the recent PGC-BD GWAS. We identified 37 independent BD-I gene-tissue associations (10 novel), 2 BD-II associations, and 2 SAB associations. Our BPD, BD-I and BD-II associations were significantly more likely to be differentially expressed in post-mortem brain tissue of BPD, BD-I and BD-II cases than we might expect by chance. Together with our pathway analysis, our results support long-standing hypotheses about bipolar disorder risk, including a role for oxidative stress and mitochondrial dysfunction, the post-synaptic density, and an enrichment of circadian rhythm and clock genes within our results.

genetics↗