High-content multi-frequency impedance cell monitoring for label-free and time-resolved cell toxicity analysis of various cell types

Here, we report a method for time-resolved, longitudinal extraction and quantitative measurement of intracellular proteins and mRNA from a variety of cell types. Cytosolic contents were repeatedly sampled from the same cell or population of cells for more than 5 d through a cell-culture substrate, incorporating hollow 150-nm-diameter nanostraws (NS) within a defined sampling region. Once extracted, the cellular contents were analyzed with conventional methods, including fluorescence, enzymatic assays (ELISA), and quantitative real-time PCR. This process was nondestructive with >95% cell viability after sampling, enabling long-term analysis. It is important to note that the measured quantities from the cell extract were found to constitute a statistically significant representation of the actual contents within the cells. Of 48 mRNA sequences analyzed from a population of cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs), 41 were accurately quantified. The NS platform samples from a select subpopulation of cells within a larger culture, allowing native cell-to-cell contact and communication even during vigorous activity such as cardiomyocyte beating. This platform was applied both to cell lines and to primary cells, including CHO cells, hiPSC-CMs, and human astrocytes derived in 3D cortical spheroids. By tracking the same cell or group of cells over time, this method offers an avenue to understand dynamic cell behavior, including processes such as induced pluripotency and differentiation.

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Label-free drug screening assay multiplexed with an orthogonal time-resolved fluorescence labeled assay

Analytical Biochemistry ◽

10.1016/j.ab.2018.11.012 ◽

2019 ◽

Vol 566 ◽

pp. 126-132

Author(s):

László Kiss ◽

Attila Cselenyák ◽

András Visegrády

Keyword(s):

Drug Screening ◽

Free Drug ◽

Label Free ◽

Time Resolved Fluorescence ◽

Screening Assay ◽

Time Resolved ◽

Drug Screening Assay

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Label-free RF biosensors for human cell dielectric spectroscopy

International Journal of Microwave and Wireless Technologies ◽

10.1017/s1759078709990614 ◽

2009 ◽

Vol 1 (6) ◽

pp. 497-504 ◽

Cited By ~ 14

Author(s):

Claire Dalmay ◽

Arnaud Pothier ◽

Mathilde Cheray ◽

Fabrice Lalloue ◽

Marie-Odile Jauberteau ◽

...

Keyword(s):

Human Cell ◽

Cell Types ◽

Label Free ◽

Microwave Frequencies ◽

Non Invasive ◽

System Cell ◽

Electromagnetic Characteristics ◽

Biosensor Chip ◽

Rf Signal

This paper presents an original biosensor chip allowing determination of intrinsic relative permittivity of biological cells at microwave frequencies. This sensor permits non-invasive cell identification and discrimination using an RF signal to probe intracellular medium of biological samples. Indeed, these sensors use an RF planar resonator that allows detection capabilities on less than 10 cells, thanks to the microscopic size of its sensitive area. Especially, measurements between 15 and 35 GHz show the ability label-free biosensors to differentiate two human cell types using their own electromagnetic characteristics. The real part of permittivity of cells changes from 20 to 48 for the nervous system cell types studied. The proposed biodetection method is detailed and we show how the accuracy and the repeatability of measurements have been improved to reach reproducible measurements.

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Pinhole microLED Array as Point Source Illumination for Miniaturized Lensless Cell Monitoring Systems

Proceedings ◽

10.3390/proceedings2130866 ◽

2018 ◽

Vol 2 (13) ◽

pp. 866 ◽

Cited By ~ 1

Author(s):

Shinta Mariana ◽

Gregor Scholz ◽

Feng Yu ◽

Agus Budi Dharmawan ◽

Iqbal Syamsu ◽

...

Keyword(s):

Image Quality ◽

Light Emitting Diode ◽

Free Cell ◽

Monitoring Systems ◽

Label Free ◽

Light Emitting ◽

Non Invasive ◽

Cell Monitoring ◽

Blue Spectral Region ◽

Led Arrays

Pinhole‐shaped light‐emitting diode (LED) arrays with dimension ranging from 100 μm down to 5 μm have been developed as point illumination sources. The proposed microLED arrays, which are based on gallium nitride (GaN) technology and emitting in the blue spectral region (λ = 465 nm), are integrated into a compact lensless holographic microscope for a non‐invasive, label‐free cell sensing and imaging. From the experimental results using single pinhole LEDs having a diameter of 90 μm, the reconstructed images display better resolution and enhanced image quality compared to those captured using a commercial surface‐mount device (SMD)‐based LED.

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Multiphoton NAD(P)H FLIM reveals metabolic changes in individual cell types of the intact cochlea upon sensorineural hearing loss

Scientific Reports ◽

10.1038/s41598-019-55329-x ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Paromita Majumder ◽

Thomas S. Blacker ◽

Lisa S. Nolan ◽

Michael R. Duchen ◽

Jonathan E. Gale

Keyword(s):

Oxidative Stress ◽

Hearing Loss ◽

Cell Model ◽

Organ Of Corti ◽

Cell Types ◽

Fluorescence Lifetime Imaging ◽

Noise Induced Hearing Loss ◽

Label Free ◽

Age Related ◽

The Individual

AbstractAn increasing volume of data suggests that changes in cellular metabolism have a major impact on the health of tissues and organs, including in the auditory system where metabolic alterations are implicated in both age-related and noise-induced hearing loss. However, the difficulty of access and the complex cyto-architecture of the organ of Corti has made interrogating the individual metabolic states of the diverse cell types present a major challenge. Multiphoton fluorescence lifetime imaging microscopy (FLIM) allows label-free measurements of the biochemical status of the intrinsically fluorescent metabolic cofactors NADH and NADPH with subcellular spatial resolution. However, the interpretation of NAD(P)H FLIM measurements in terms of the metabolic state of the sample are not completely understood. We have used this technique to explore changes in metabolism associated with hearing onset and with acquired (age-related and noise-induced) hearing loss. We show that these conditions are associated with altered NAD(P)H fluorescence lifetimes, use a simple cell model to confirm an inverse relationship between τbound and oxidative stress, and propose such changes as a potential index of oxidative stress applicable to all mammalian cell types.

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Label-free prediction of Cell Painting from brightfield images

10.1101/2021.11.05.467394 ◽

2021 ◽

Author(s):

Jan Oscar Cross-Zamirski ◽

Elizabeth Mouchet ◽

Guy Williams ◽

Carola-Bibiane Schönlieb ◽

Riku Turkki ◽

...

Keyword(s):

Pearson Correlation ◽

Ground Truth ◽

Free Cell ◽

Label Free ◽

Biological Interest ◽

Genetic Perturbations ◽

Toxicity Analysis ◽

Model Training ◽

Downstream Analysis ◽

Cellular Components

Cell Painting is a high-content image-based assay which can reveal rich cellular morphology and is applied in drug discovery to predict bioactivity, assess toxicity and understand diverse mechanisms of action of chemical and genetic perturbations. In this study, we investigate label-free Cell Painting by predicting the five fluorescent Cell Painting channels from paired brightfield z-stacks using deep learning models. We train and validate the models with a dataset representing 1000s of pan-assay interference compounds sampled from 17 unique batches. The model predictions are evaluated using a test set from two additional batches, treated with compounds comprised from a publicly available phenotypic set. In addition to pixel-level evaluation, we process the label-free Cell Painting images with a segmentation-based feature-extraction pipeline to understand whether the generated images are useful in downstream analysis. The mean Pearson correlation coefficient (PCC) of the images across all five channels is 0.84. Without actually incorporating these features into the model training we achieved a mean correlation of 0.45 from the features extracted from the images. Additionally we identified 30 features which correlated greater than 0.8 to the ground truth. Toxicity analysis on the label-free Cell Painting resulted a sensitivity of 62.5% and specificity of 99.3% on images from unseen batches. Additionally, we provide a breakdown of the feature profiles by channel and feature type to understand the potential and limitation of the approach in morphological profiling. Our findings demonstrate that label-free Cell Painting has potential above the improved visualization of cellular components, and it can be used for downstream analysis. The findings also suggest that label-free Cell Painting could allow for repurposing the imaging channels for other non-generic fluorescent stains of more targeted biological interest, thus increasing the information content of the assay.

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Deep Learning Identifies Cardiomyocyte Nuclei in Murine Tissue with High Precision

10.1101/2020.01.10.900936 ◽

2020 ◽

Author(s):

Shah R. Ali ◽

Dan Nguyen ◽

Brandon Wang ◽

Steven Jiang ◽

Hesham A. Sadek

Keyword(s):

Deep Learning ◽

Cell Types ◽

Label Cell ◽

Biological Research ◽

Mouse Heart ◽

Specific Cell ◽

Label Free ◽

Structural Protein ◽

Mammalian Tissues ◽

Murine Tissue

ABSTRACTProper identification and annotation of cells in mammalian tissues is of paramount importance to biological research. Various approaches are currently used to identify and label cell types of interest in complex tissues. In this report, we generated an artificial intelligence (AI) deep learning model that uses image segmentation to predict cardiomyocyte nuclei in mouse heart sections without a specific cardiomyocyte nuclear label. This tool can annotate cardiomyocytes highly sensitively and specifically (AUC 0.94) using only cardiomyocyte structural protein immunostaining and a global nuclear stain. We speculate that our method is generalizable to other tissues to annotate specific cell types and organelles in a label-free way.

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Methods and applications of label-free cell-based systems

KnE Engineering ◽

10.18502/keg.v0i0.493 ◽

2016 ◽

Vol 1 (1) ◽

Author(s):

Joachim Wiest

Keyword(s):

Environmental Monitoring ◽

Morphological Changes ◽

Free Cell ◽

Living Cells ◽

Label Free ◽

Controlled System ◽

Chip Technology ◽

Cell Monitoring ◽

A Cell ◽

On Chip

Label-free monitoring of living cells is used in various applications such as drug development, toxicology, regenerative medicine or environmental monitoring. The most prominent methods for monitoring the extracellular acidification, oxygen consumption, electrophysiological activity and morphological changes of living cells are described. Furthermore, the intelligent mobile lab (IMOLA) – a computer controlled system integrating cell monitoring and automated cell cultivation – is described as an example of a cell-based system for microphysiometry. Results from experiments in the field of environmental monitoring using algae are presented. An outlook toward the development of an organ-on-chip technology is given.

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