Biology subjects

Jacobi, A.

Publications and source records attributed to Jacobi, A..

14 recordsLinked to original sources

bioRxiv2026

Impact of chemotherapy on leukocyte stiffness -A longitudinal RT-DC study in a breast cancer patient

BackgroundThe physical properties of leukocytes, such as cell size and stiffness, are critical for their circulation in microcapillary networks where rapid shape changes are required to squeeze through vascular constrictions. Alterations in the cells physical phenotype can promote venous thromboembolism (VTE), a common cause of death in cancer patients receiving chemotherapy. While biochemical VTE predictors are well studied, physical properties of blood cells receive less attention. MethodsUsing real-time deformability cytometry (RT-DC), we monitored for the first time the physical phenotype of leukocytes in a longitudinal study of a breast cancer patient treated with epirubicin/cyclophosphamide (EC) and paclitaxel (Pax). ResultsThe leukocyte counts extracted from RT-DC were in good agreement with standard clinical leukograms and EC had no immediate effect on leukocyte properties. However, Pax caused a significant softening of granulo/monocytes and a stiffening of lymphocytes immediately after administration. Leukocyte size was constant throughout the therapy, but we observed an overall increase in leukocyte stiffness, which was restored to normal values 45 weeks post treatment. ConclusionTaken together, our data reveal chemotherapy-induced specific alterations of leukocyte stiffness potentially critical for microcirculation. Thus, RT-DC measurements can add important, yet currently not available information to VTE prediction in cancer patients.

biophysics↗

bioRxiv2026

A Unifying Mechanism for Synaptic Amyloid beta Toxicity Beta Adrenergic Potentiation of the Ca2+ Channel CaV1.2 by Amyloid beta

Amyloid {beta} peptides (A{beta}) trigger Alzheimers disease (AD) but how has remained elusive. A{beta} stimulates the {beta}2 adrenergic receptor ({beta}2AR), which forms a unique signaling complex with the L-type Ca2+ channel (LTCC) CaV1.2. LTCCs have been implicated in the etiology of dementia and AD. We show that A{beta} acutely potentiates CaV1.2 via the {beta}2AR, which triggers postsynaptic recruitment of Ca2+ permeable (CP) AMPARs in hippocampal cultures and impairs LTP in hippocampal slices within minutes. The long-term consequence is a loss of postsynaptic structure of glutamatergic synapses and neurotoxicity. Disrupting this signaling cascade with highly specific tools prevented all of these effects, unifying a number of currently divergent findings on A{beta} synaptotoxicity including dysregulation of AMPARs and synaptic plasticity. TEASERAmyloid {beta} peptide is the primary pathological agent in Alzheimers disease. It affects the nanoscale structure and function of glutamatergic synapses. The molecular mechanisms are largely unknown except for identification of several binding proteins including the {beta}2 adrenergic receptor. We show that this binding potently (EC50<100 nM) augments Ca2+ influx through the L-type Ca channel CaV1.2. This effect leads to improper recruitment of Ca2+-permeable glutamate receptors to postsynaptic sites (EC50<100 nM), synaptic dysfunction and ultimately neuronal death. This work identifies an essential mechanism in amyloid {beta} neurotoxicity and explains many of the observed postsynaptic alterations. HighlightsImmediate effects of A{beta}-induced stimulation of {beta}2AR on Cav1.2: O_LIA{beta} induces phosphorylation of Cav1.2 on S1928 by PKA C_LIO_LIA{beta} augments Cav1.2 activity via {beta}2AR-induced S1928 phosphorylation within seconds C_LI A{beta}-induced {beta}2AR - Cav1.2 signaling has the following synaptotoxic effects. O_LIA{beta} induces postsynaptic accumulation of Ca-permeable AMPARs via {beta}2AR - Cav1.2 signaling within 20 min C_LIO_LIA{beta} impairs long-term potentiation (LTP) via {beta}2AR - Cav1.2 signaling C_LIO_LIA{beta} impairs postsynaptic structure and neuronal viability over 24 h C_LIO_LIPotency of A{beta} in all the above effects is very high (100 nM A{beta} is saturating!) C_LIO_LIAll effects are prevented in S1928A KI mice and acute displaces {beta}2AR from Cav1.2 with tat-Pep1923 C_LI

neuroscience↗

bioRxiv2026

Single-Cell and Tissue-Specific CRISPR Editing Analyses Unveil New Insights to Off-Targets and Translocations

CRISPR-Cas9 holds promise for treating genetic disease, but rare off-target mutations and structural variants remain as key safety concerns, especially at scales relevant to therapy. We established workflows to resolve Cas9 off-target activity in vitro at single-cell resolution and in vivo across different tissues. Using clonally expanded electroporated mouse embryos and embryonic stem cells, we reveal that individual cells exhibit unique off-target and translocation profiles, including events missed in bulk analyses. Integrating single-cell editing with chromatin accessibility, transcription, and DNA methylation measurements suggested that sequence-independent features modulate Cas9 access and cleavage, with preferential editing in regions characterized by open chromatin and lower methylation. In Cas9-inducible mouse models, editing analyses revealed organ-distinct off-target spectra, DNA repair pathway usage, indel patterns, and markedly varying translocation propensity between tissues. These findings demonstrate that off-target activity is heterogeneous across cells and context-dependent across organs, motivating sensitive single-cell analyses and organ-specific evaluation in preclinical development to more accurately assess risk and improve the safety of CRISPR-based genomic medicines.

genomics↗

bioRxiv2022

Temporal single cell atlas of non-neuronal retinal cells reveals dynamic, coordinated multicellular responses to central nervous system injury

Non-neuronal cells play key roles in the complex cellular interplay that follows central nervous system (CNS) insult. To understand this interplay at a tissue level, we generated a single-cell atlas of immune, glial and retinal pigment epithelial cells from adult mouse retina before and at multiple time points after axonal transection (optic nerve crush; ONC), identifying rare and undescribed subsets, and delineating changes in cell composition, expression programs, and interactions. Computational analysis charted an inflammatory cascade after injury with three phases. The early phase consisted of reactivation of retinal macroglia and microglia, providing chemotactic signals for immune infiltration, concurrent with infiltration of CCR2+ monocytes from the circulation. In the second phase, these differentiated to macrophage subsets resembling resident border-associated macrophages. In parallel, a multicellular interferon program, likely driven by microglia-derived type-I interferon, was synchronously activated across resident glia, expanding beyond rare interferon-responding subsets of glia unexpectedly present in the naive retina. Our findings provide insights regarding post-injury CNS tissue dynamics and a framework to decipher cellular circuitry, spatial relationships and molecular interactions following tissue injury.

immunology↗

bioRxiv2022

Core Transcription Programs Controlling Injury-Induced Neurodegeneration of Retinal Ganglion Cells

Neurodegenerative diseases are characterized by neuronal death and regenerative failure. However, gene regulatory programs governing how initial neuronal injuries lead to neuronal death remain poorly understood. In adult mice, optic nerve crush (ONC) injury, which severs all axons of retinal ganglion cells (RGCs), results in massive death of axotomized RGCs and regenerative failure of survivors. We performed an in vivo CRISPR/Cas9-based genome-wide screen of 1893 transcription factors (TFs) to seek repressors of RGC survival and axon regeneration following ONC. In parallel, we profiled the epigenetic and transcriptional landscapes of injured RGCs by ATAC-seq and RNA-seq to identify critical injury responsive TFs and their targets. Remarkably, these independent analyses converged on a set of four ATF/CEBP transcription factors - ATF3, ATF4, C/EBP{gamma} and CHOP (Ddit3) - as critical regulators of survival. Further studies indicate that these TFs contribute to two pro-death transcriptional programs: ATF3/CHOP preferentially regulate pathways activated by cytokines and innate immunity, whereas ATF4/C/EBP{gamma} regulate pathways engaged by intrinsic neuronal stressors. Manipulation of these TFs also protects RGCs in an experimental model of glaucoma, a prevalent disease in which RGCs die. Together, our results reveal core transcription programs that transform an initial axonal insult into a degenerative result and suggest novel strategies for treating neurodegenerative diseases.

neuroscience↗

bioRxiv2022

Overlapping transcriptional programs promote survival and axonal regeneration of injured retinal ganglion cells

Injured neurons in the adult mammalian central nervous system often die and seldom regenerate axons. To uncover transcriptional pathways that could ameliorate these disappointing responses we analyzed three interventions that increase survival and regeneration of mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC) injury, albeit not to a clinically useful extent. We assessed gene expression in each of 46 RGC types by single cell transcriptomics following ONC and treatment. We also compared RGCs that regenerated to those that survived but did not regenerate. Each intervention enhanced survival of most RGC types, but type-independent axon regeneration required manipulation of multiple pathways. Distinct computational methods converged on separate sets of genes selectively expressed by RGCs likely to be dying, surviving, or regenerating. Overexpression of genes associated with the regeneration program enhanced axon regeneration in vivo, indicating that mechanistic analysis can be used to identify novel methods for promoting regeneration of injured neurons.

neuroscience↗

bioRxiv2021

Unified classification of mouse retinal ganglion cells using function, morphology, and gene expression

Classification and characterization of neuronal types are critical for understanding their function and dysfunction. Neuronal classification schemes typically rely on measurements of electrophysiological, morphological, and molecular features, but aligning such datasets has been challenging. Here, we present a unified classification of mouse retinal ganglion cells (RGCs), the sole retinal output neurons. We used visually-evoked responses to classify 1859 mouse RGCs into 42 types. We also obtained morphological or transcriptomic data from subsets and used these measurements to align the functional classification to publicly available morphological and transcriptomic data sets. We created an online database that allows users to browse or download the data and to classify RGCs from their light responses using a machine learning algorithm. This work provides a resource for studies of RGCs, their upstream circuits in the retina, and their projections in the brain, and establishes a framework for future efforts in neuronal classification and open data distribution.

neuroscience↗

bioRxiv2020

AIDeveloper: deep learning image classification in life science and beyond

Publications on artificial intelligence (AI)-based image analysis have increased drastically in recent years. However, all applications use individual solutions highly specialized for a particular task. Here, we present an easy-to-use, adaptable, open source software, called AIDeveloper (AID) to train neural nets (NN) for image classification without the need for programming. The software provides a variety of NN-architectures that can be simply selected for training. AID allows the user to apply trained models on new data, obtain metrics for classification performance, and export final models to different formats. The working principles of AID are first illustrated by training a convolutional neural net (CNN) on a large dataset consisting of images of different objects (CIFAR-10). We further explore the potential of AID by training a model to distinguish areas of differentiated and non-differentiated mesenchymal stem cells (MSCs) in culture. Additionally, we compare a conventional clinical whole blood cell count with a whole blood cell count performed by an NN-trained, using a dataset of more than 1.2 million images obtained by real-time deformability cytometry, delivering comparable results. Finally, we demonstrate how AID can be used for label-free classification of B- and T-cells derived from human blood, which currently requires costly and time-consuming sample preparation. Thus, AID can empower anyone to develop, train, and apply NNs for image classification. Moreover, models can be generated by non-programmers, exported, and used on different devices, which allows for an interdisciplinary use.

bioinformatics↗

bioRxiv2019

Using real-time fluorescence and deformability cytometry and deep learning to transfer molecular specificity to label-free sorting

The identification and separation of specific cells from heterogeneous populations is an essential prerequisite for further analysis or use. Conventional passive and active separation approaches rely on fluorescent or magnetic tags introduced to the cells of interest through molecular markers. Such labeling is time- and cost-intensive, can alter cellular properties, and might be incompatible with subsequent use, for example, in transplantation. Alternative label-free approaches utilizing morphological or mechanical features are attractive, but lack molecular specificity. Here we combine image-based real-time fluorescence and deformability cytometry (RT-FDC) with downstream cell sorting using standing surface acoustic waves (SSAW). We demonstrate basic sorting capabilities of the device by separating cell mimics and blood cell types based on fluorescence as well as deformability and other image parameters. The identification of blood sub-populations is enhanced by flow alignment and deformation of cells in the microfluidic channel constriction. In addition, the classification of blood cells using established fluorescence-based markers provides hundreds of thousands of labeled cell images used to train a deep neural network. The trained algorithm, with latency optimized to below 1 ms, is then used to identify and sort unlabeled blood cells at rates of 100 cells/sec. This approach transfers molecular specificity into label-free sorting and opens up new possibilities for basic biological research and clinical therapeutic applications.

biophysics↗

bioRxiv2019

Single-cell profiles of retinal neurons differing in resilience to injury reveal neuroprotective genes

Neuronal types in the central nervous system differ dramatically in their resilience to injury or insults. Here we studied the selective resilience of mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC), which severs their axons and leads to death of ~80% of RGCs within 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 46 RGC types in adult retina. We then tracked their survival after ONC, characterized transcriptomic, physiological, and morphological changes that preceded degeneration, and identified genes selectively expressed by each type. Finally, using loss- and gain-of-function assays in vivo, we showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury, and demonstrates that differential gene expression can be used to reveal molecular targets for intervention.

neuroscience↗

bioRxiv2018

Spheroid culture of mesenchymal stromal cells results in morpho-rheological properties appropriate for improved microcirculation

Human bone marrow mesenchymal stromal cells (MSCs) have been used in clinical trials for the treatment of systemic inflammatory diseases due to their regenerative and immunomodulatory properties. However, intravenous administration of MSCs is hampered by cell trapping within the pulmonary capillary networks. Here, we hypothesize that traditional twodimensional (2D) plastic-adherent cell expansion fails to result in appropriate morphorheological properties required for cell-circulation. To address this issue, we adapted a novel method to culture MSCs in non-adherent three-dimensional (3D) spheroids (mesenspheres). The biological properties of mesensphere-cultured MSCs remained identical to conventional 2D cultures. Morpho-rheological analyses revealed a smaller size and lower cell stiffness of mesensphere-derived MSCs compared to plastic-adherent MSCs, measured using real-time deformability cytometry (RT-DC) and atomic force microscopy, resulting in an increased ability to pass through micro-constrictions in an ex vivo microcirculation assay. This ability was confirmed in vivo by analysis of cell accumulation in various organ capillary networks after intravenous injection of mesensphere-derived MSCs in mouse. Our findings generally identify cellular morpho-rheological properties as attractive targets to improve microcirculation and specifically suggest mesensphere cultures as a promising approach for optimized MSC-based therapies.

biophysics↗

bioRxiv2018

Standardized microgel beads as elastic cell mechanical probes

Cell mechanical measurements are gaining increasing interest in biological and biomedical studies. However, there are no standardized calibration particles available that permit the cross-comparison of different measurement techniques operating at different stresses and time-scales. Here we present the rational design, production, and comprehensive characterization of poly-acylamide (PAAm) microgel beads mimicking biological cells. We produced mono-disperse beads at rates of 20 - 60 kHz by means of a microfluidic droplet generator, where the pre-gel composition was adjusted to tune the beads elasticity in the range of cell and tissue relevant mechanical properties. We verified bead homogeneity by optical diffraction tomography and Brillouin microscopy. Consistent elastic behavior of microgel beads at different shear rates was confirmed by AFM-enabled nanoindentation and real-time deformability cytometry (RT-DC). The remaining inherent variability in elastic modulus was rationalized using polymer theory and effectively reduced by sorting based on forward-scattering using conventional flow cytometry. Our results show that PAAm microgel beads can be standardized as mechanical probes, to serve not only for validation and calibration of cell mechanical measurements, but also as cell-scale stress sensors.\n\nSignificance StatementOften vastly different cell mechanical properties are reported even for the same cell type when employing different measurement techniques. This discrepancy shows the urgent need for standardized calibration particles to cross-compare and validate techniques. Microgel beads can serve this purpose, but they have to fulfil specific requirements such as homogeneity, sizes and elasticities in the range of the cells, and they have to provide comparable results independent of the method applied. Here we demonstrate the standardized production of polyacrylamide microgel beads with all the features an elastic cell-mimic should have. These can not only be used as method calibration particles, but can also serve as cell-scale sensors to quantify normal and shear stresses exerted by other cells and inside tissues, enabling many new applications.

biophysics↗

bioRxiv2017

Real-time fluorescence and deformability cytometry - flow cytometry goes mechanics

Cell mechanical characterization has recently approached the throughput of conventional flow cytometers. However, this very sensitive, label-free approach still lacks the specificity of molecular markers. Here we combine real-time 1D-imaging fluorescence and deformability cytometry (RT-FDC) to merge the two worlds in one instrument -- opening many new research avenues. We demonstrate its utility using sub-cellular fluorescence localization to identify mitotic cells and test for their mechanical changes in an RNAi screen.

biophysics↗

bioRxiv2017

Detection Of Human Disease Conditions By Single-Cell Morpho-Rheological Phenotyping Of Whole Blood

Blood is arguably the most important bodily fluid and its analysis provides crucial health status information. A first routine measure to narrow down diagnosis in clinical practice is the differential blood count, determining the frequency of all major blood cells. What is lacking to advance initial blood diagnostics is an unbiased and quick functional assessment of blood that can narrow down the diagnosis and generate specific hypotheses. To address this need, we introduce the continuous, cell-by-cell morpho-rheological (MORE) analysis of whole blood, without labeling, enrichment or separation, at rates of 1,000 cells/sec. In a drop of blood we can identify all major blood cells and characterize their pathological changes in several disease conditions in vitro and in patient samples. This approach takes previous results of mechanical studies on specifically isolated blood cells to the level of application directly in whole blood and adds a functional dimension to conventional blood analysis.

biophysics↗