Browse
Submit Data
Databases
API
Help

Dataset Information

24 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Resolving immune cells with patrolling behaviour by magnetic resonance time-lapse single cell tracking

ABSTRACT:

Background

Immune cells show distinct motion patterns that change upon inflammatory stimuli. Monocytes patrol the vasculature to screen for pathogens, thereby exerting an early task of innate immunity. Here, we aimed to non-invasively analyse single patrolling monocyte behaviour upon inflammatory stimuli.

Methods

We used time-lapse Magnetic Resonance Imaging (MRI) of the murine brain to dynamically track single patrolling monocytes within the circulation distant to the actual site of inflammation in different inflammatory conditions, ranging from a subcutaneous pellet model to severe peritonitis and bacteraemia.

Findings

Single patrolling immune cells with a velocity of <1 µm/s could be detected and followed dynamically using time-lapse MRI. We show, that due to local and systemic stimuli the slowly patrolling behaviour of monocytes is altered systemically and differs with type, duration and strength of the underlying stimulus.

Interpretation

Using time-lapse MRI, it is now possible to investigate the behaviour of single circulating monocytes over the course of the systemic immune response. Monocyte patrolling behaviour is altered systemically even before the onset of clinical symptoms distant to and depending on the underlying inflammatory stimulus.

Funding

This study was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - CRC 1009 - 194468054 to AZ, CF and - CRC 1450 - 431460824 to MM, SN, HB, AZ, CF, the Joachim Herz Foundation (Add-on Fellowship for Interdisciplinary Life Sciences to MM), the Interdisciplinary Centre for Clinical Research (IZKF, core unit PIX) and the Medical Faculty of the University of Muenster (MEDK fellowship to FF and IF).

SUBMITTER: Masthoff M

PROVIDER: S-EPMC8581510 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Robust single-particle tracking in live-cell time-lapse sequences.

Project description:Single-particle tracking (SPT) is often the rate-limiting step in live-cell imaging studies of subcellular dynamics. Here we present a tracking algorithm that addresses the principal challenges of SPT, namely high particle density, particle motion heterogeneity, temporary particle disappearance, and particle merging and splitting. The algorithm first links particles between consecutive frames and then links the resulting track segments into complete trajectories. Both steps are formulated as global combinatorial optimization problems whose solution identifies the overall most likely set of particle trajectories throughout a movie. Using this approach, we show that the GTPase dynamin differentially affects the kinetics of long- and short-lived endocytic structures and that the motion of CD36 receptors along cytoskeleton-mediated linear tracks increases their aggregation probability. Both applications indicate the requirement for robust and complete tracking of dense particle fields to dissect the mechanisms of receptor organization at the level of the plasma membrane.

| S-EPMC2747604 | biostudies-literature

Label free, quantitative single-cell fate tracking of time-lapse movies.

Project description:Historically, the ability to perform multi-day time-lapse imaging of adherent cells required expensive and specialized microscopy equipment. As byproduct of this cost, many labs would synchronize cells using inhibitors such as hydroxyurea and thymidine, and or use fluorescent biosensors to minimize time required on the microscope. These methods introduce significant artefacts including phototoxicity, increased DNA replication stress and mitotic defects, thereby limiting the ability to characterize various cell cycle phenotypes. However, increased access to low cost live cell microscopes has removed many of the economic barriers thereby allowing multi-day imaging on asynchronous cells on a regular basis. Here we describe our protocol for manually tracking individual cell fates across multiple generations of random daughter cells using only low toxicity brightfield based imaging. Importantly, our pipeline relies on the free open-source software ImageJ/Fiji and an easy to use Microsoft Excel spreadsheet. Furthermore, annotated files can be saved to allow later recall of any individual cell. In summary, our method provides quantitative data on interphase and mitotic transit time, points of cell cycle arrest and critically, the ability to link these events with cell fate.

| S-EPMC6838936 | biostudies-literature

Resolving the role of plant glutamate dehydrogenase. I. In vivo real time nuclear magnetic resonance spectroscopy experiments.

Project description:In higher plants the glutamate dehydrogenase (GDH) enzyme catalyzes the reversible amination of 2-oxoglutarate to form glutamate, using ammonium as a substrate. For a better understanding of the physiological function of GDH either in ammonium assimilation or in the supply of 2-oxoglutarate, we used transgenic tobacco (Nicotiana tabacum L.) plants overexpressing the two genes encoding the enzyme. An in vivo real time (15)N-nuclear magnetic resonance (NMR) spectroscopy approach allowed the demonstration that, when the two GDH genes were overexpressed individually or simultaneously, the transgenic plant leaves did not synthesize glutamate in the presence of ammonium when glutamine synthetase (GS) was inhibited. In contrast we confirmed that the primary function of GDH is to deaminate Glu. When the two GDH unlabeled substrates ammonium and Glu were provided simultaneously with either [(15)N]Glu or (15)NH(4)(+) respectively, we found that the ammonium released from the deamination of Glu was reassimilated by the enzyme GS, suggesting the occurrence of a futile cycle recycling both ammonium and Glu. Taken together, these results strongly suggest that the GDH enzyme, in conjunction with NADH-GOGAT, contributes to the control of leaf Glu homeostasis, an amino acid that plays a central signaling and metabolic role at the interface of the carbon and nitrogen assimilatory pathways. Thus, in vivo NMR spectroscopy appears to be an attractive technique to follow the flux of metabolites in both normal and genetically modified plants.

| S-EPMC2759343 | biostudies-literature

Study of Wound Healing Dynamics by Single Pseudo-Particle Tracking in Phase Contrast Images Acquired in Time-Lapse.

Project description:Cellular contacts modify the way cells migrate in a cohesive group with respect to a free single cell. The resulting motion is persistent and correlated, with cells' velocities self-aligning in time. The presence of a dense agglomerate of cells makes the application of single particle tracking techniques to define cells dynamics difficult, especially in the case of phase contrast images. Here, we propose an original pipeline for the analysis of phase contrast images of the wound healing scratch assay acquired in time-lapse, with the aim of extracting single particle trajectories describing the dynamics of the wound closure. In such an approach, the membrane of the cells at the border of the wound is taken as a unicum, i.e., the wound edge, and the dynamics is described by the stochastic motion of an ensemble of points on such a membrane, i.e., pseudo-particles. For each single frame, the pipeline of analysis includes: first, a texture classification for separating the background from the cells and for identifying the wound edge; second, the computation of the coordinates of the ensemble of pseudo-particles, chosen to be uniformly distributed along the length of the wound edge. We show the results of this method applied to a glioma cell line (T98G) performing a wound healing scratch assay without external stimuli. We discuss the efficiency of the method to assess cell motility and possible applications to other experimental layouts, such as single cell motion. The pipeline is developed in the Python language and is available upon request.

| S-EPMC7996888 | biostudies-literature

Quantitative time-lapse fluorescence microscopy in single cells.

Project description:The cloning of green fluorescent protein (GFP) 15 years ago revolutionized cell biology by permitting visualization of a wide range of molecular mechanisms within living cells. Though initially used to make largely qualitative assessments of protein levels and localizations, fluorescence microscopy has since evolved to become highly quantitative and high-throughput. Computational image analysis has catalyzed this evolution, enabling rapid and automated processing of large datasets. Here, we review studies that combine time-lapse fluorescence microscopy and automated image analysis to investigate dynamic events at the single-cell level. We highlight examples where single-cell analysis provides unique mechanistic insights into cellular processes that cannot be otherwise resolved in bulk assays. Additionally, we discuss studies where quantitative microscopy facilitates the assembly of detailed 4D lineages in developing organisms. Finally, we describe recent advances in imaging technology, focusing especially on platforms that allow the simultaneous perturbation and quantitative monitoring of biological systems.

| S-EPMC3137897 | biostudies-literature

Bacteria tracking by in vivo magnetic resonance imaging.

Project description:BackgroundDifferent non-invasive real-time imaging techniques have been developed over the last decades to study bacterial pathogenic mechanisms in mouse models by following infections over a time course. In vivo investigations of bacterial infections previously relied mostly on bioluminescence imaging (BLI), which is able to localize metabolically active bacteria, but provides no data on the status of the involved organs in the infected host organism. In this study we established an in vivo imaging platform by magnetic resonance imaging (MRI) for tracking bacteria in mouse models of infection to study infection biology of clinically relevant bacteria.ResultsWe have developed a method to label Gram-positive and Gram-negative bacteria with iron oxide nano particles and detected and pursued these with MRI. The key step for successful labeling was to manipulate the bacterial surface charge by producing electro-competent cells enabling charge interactions between the iron particles and the cell wall. Different particle sizes and coatings were tested for their ability to attach to the cell wall and possible labeling mechanisms were elaborated by comparing Gram-positive and -negative bacterial characteristics. With 5-nm citrate-coated particles an iron load of 0.015 ± 0.002 pg Fe/bacterial cell was achieved for Staphylococcus aureus. In both a subcutaneous and a systemic infection model induced by iron-labeled S. aureus bacteria, high resolution MR images allowed for bacterial tracking and provided information on the morphology of organs and the inflammatory response.ConclusionLabeled with iron oxide particles, in vivo detection of small S. aureus colonies in infection models is feasible by MRI and provides a versatile tool to follow bacterial infections in vivo. The established cell labeling strategy can easily be transferred to other bacterial species and thus provides a conceptual advance in the field of molecular MRI.

| S-EPMC3686665 | biostudies-literature

Resolving Cytosolic Diffusive States in Bacteria by Single-Molecule Tracking.

Project description:The trajectory of a single protein in the cytosol of a living cell contains information about its molecular interactions in its native environment. However, it has remained challenging to accurately resolve and characterize the diffusive states that can manifest in the cytosol using analytical approaches based on simplifying assumptions. Here, we show that multiple intracellular diffusive states can be successfully resolved if sufficient single-molecule trajectory information is available to generate well-sampled distributions of experimental measurements and if experimental biases are taken into account during data analysis. To address the inherent experimental biases in camera-based and MINFLUX-based single-molecule tracking, we use an empirical data analysis framework based on Monte Carlo simulations of confined Brownian motion. This framework is general and adaptable to arbitrary cell geometries and data acquisition parameters employed in two-dimensional or three-dimensional single-molecule tracking. We show that, in addition to determining the diffusion coefficients and populations of prevalent diffusive states, the timescales of diffusive state switching can be determined by stepwise increasing the time window of averaging over subsequent single-molecule displacements. Time-averaged diffusion analysis of single-molecule tracking data may thus provide quantitative insights into binding and unbinding reactions among rapidly diffusing molecules that are integral for cellular functions.

| S-EPMC6531849 | biostudies-literature

Resolving Cytosolic Diffusive States in Bacteria by Single-Molecule Tracking.

| S-EPMC6531849 | biostudies-literature

Resolving Cytosolic Diffusive States in Bacteria by Single-Molecule Tracking.

| S-EPMC6531849 | biostudies-literature

Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations.

Project description:Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image sequences, each spanning approximately 3.5 days, were generated with accompanying ground truths for C2C12 myoblast cells cultured under 4 different media conditions, including with fibroblast growth factor 2 (FGF2), bone morphogenetic protein 2 (BMP2), FGF2 + BMP2, and control (no growth factor). The ground truths generated contain information for tracking at least 3 parent cells and their descendants within these datasets and were validated using a two-tier system of manual curation. This comprehensive, validated dataset will be useful in advancing the development of computer-aided cell tracking algorithms and function as a benchmark, providing an invaluable opportunity to deepen our understanding of individual and population-based cell dynamics for biomedical research.

| S-EPMC6233481 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data