scholarly journals Visualizing Metabolic Processes at the Single-Cell Level - Using Genetically Encoded Biosensor and Biomarker

2021 ◽  
pp. 276-314
Author(s):  
Elena Locci ◽  
Silvia Raymond
Keyword(s):  
Artificial Intelligence ◽  
Endothelial Cells ◽  
Blood Vessel ◽  
Single Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Wide Range ◽  
Keywords Cancer ◽  
Glycolysis Process ◽  
Genetically Encoded Biosensor

Understanding cellular metabolism (how cells use energy) can be key in treating a wide range of diseases, including vascular disease and cancer. Although many techniques can measure these processes in tens of thousands of cells, researchers have not been able to measure them at the single-cell level. Researchers have used a genetically encoded biosensor with artificial intelligence to measure glycolysis. (Process of converting glucose to energy, single endothelial cells, blood vessel cells). Keywords: Cancer; Cells; Tissues, Tumors; Prevention, Prognosis; Diagnosis; Imaging; Screening; Treatment; Management

scholarly journals Process of Converting Glucose to Energy, Single Endothelial Cells and Blood Vessel Cells

2021 ◽  
pp. 261-300
Author(s):  
Ricardo Gobato ◽  
Abhijit Mitra
Keyword(s):  
Artificial Intelligence ◽  
Endothelial Cells ◽  
Blood Vessel ◽  
Cancer Cells ◽  
Single Cell Level ◽  
Cell Level ◽  
Wide Range ◽  
Keywords Cancer ◽  
Glycolysis Process ◽  
Genetically Encoded Biosensor

Understanding cellular metabolism (how cells use energy) can be key in treating a wide range of diseases, including vascular disease and cancer. Although many techniques can measure these processes in tens of thousands of cells, researchers have not been able to measure them at the single-cell level. Researchers have used a genetically encoded biosensor with artificial intelligence to measure glycolysis. (Process of converting glucose to energy, single endothelial cells, blood vessel cells). Keywords: Cancer; Cells; Tissues; Tumors; Prevention; Prognosis; Diagnosis; Imaging; Screening, Treatment; Management

scholarly journals Mito Hacker: a set of tools to enable high-throughput analysis of mitochondrial network morphology

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ali Rohani ◽  
Jennifer A. Kashatus ◽  
Dane T. Sessions ◽  
Salma Sharmin ◽  
David F. Kashatus
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Data Science ◽  
Structural Information ◽  
Morphological Changes ◽  
Mitochondrial Morphology ◽  
Single Cell Level ◽  
Mitochondrial Network ◽  
Cell Level ◽  
Wide Range

Abstract Mitochondria are highly dynamic organelles that can exhibit a wide range of morphologies. Mitochondrial morphology can differ significantly across cell types, reflecting different physiological needs, but can also change rapidly in response to stress or the activation of signaling pathways. Understanding both the cause and consequences of these morphological changes is critical to fully understanding how mitochondrial function contributes to both normal and pathological physiology. However, while robust and quantitative analysis of mitochondrial morphology has become increasingly accessible, there is a need for new tools to generate and analyze large data sets of mitochondrial images in high throughput. The generation of such datasets is critical to fully benefit from rapidly evolving methods in data science, such as neural networks, that have shown tremendous value in extracting novel biological insights and generating new hypotheses. Here we describe a set of three computational tools, Cell Catcher, Mito Catcher and MiA, that we have developed to extract extensive mitochondrial network data on a single-cell level from multi-cell fluorescence images. Cell Catcher automatically separates and isolates individual cells from multi-cell images; Mito Catcher uses the statistical distribution of pixel intensities across the mitochondrial network to detect and remove background noise from the cell and segment the mitochondrial network; MiA uses the binarized mitochondrial network to perform more than 100 mitochondria-level and cell-level morphometric measurements. To validate the utility of this set of tools, we generated a database of morphological features for 630 individual cells that encode 0, 1 or 2 alleles of the mitochondrial fission GTPase Drp1 and demonstrate that these mitochondrial data could be used to predict Drp1 genotype with 87% accuracy. Together, this suite of tools enables the high-throughput and automated collection of detailed and quantitative mitochondrial structural information at a single-cell level. Furthermore, the data generated with these tools, when combined with advanced data science approaches, can be used to generate novel biological insights.

scholarly journals Spatiotemporal mapping of bacterial membrane potential responses to extracellular electron transfer

2020 ◽  
Vol 117 (33) ◽  
pp. 20171-20179 ◽  
Author(s):  
Sahand Pirbadian ◽  
Marko S. Chavez ◽  
Mohamed Y. El-Naggar
Keyword(s):  
Electron Transfer ◽  
Membrane Potential ◽  
Single Cell ◽  
Electrochemical Techniques ◽  
Model Organisms ◽  
Extracellular Electron Transfer ◽  
Single Cell Level ◽  
Cell Level ◽  
Membrane Hyperpolarization ◽  
Wide Range

Extracellular electron transfer (EET) allows microorganisms to gain energy by linking intracellular reactions to external surfaces ranging from natural minerals to the electrodes of bioelectrochemical renewable energy technologies. In the past two decades, electrochemical techniques have been used to investigate EET in a wide range of microbes, with emphasis on dissimilatory metal-reducing bacteria, such asShewanella oneidensisMR-1, as model organisms. However, due to the typically bulk nature of these techniques, they are unable to reveal the subpopulation variation in EET or link the observed electrochemical currents to energy gain by individual cells, thus overlooking the potentially complex spatial patterns of activity in bioelectrochemical systems. Here, to address these limitations, we use the cell membrane potential as a bioenergetic indicator of EET byS. oneidensisMR-1 cells. Using a fluorescent membrane potential indicator during in vivo single-cell-level fluorescence microscopy in a bioelectrochemical reactor, we demonstrate that membrane potential strongly correlates with EET. Increasing electrode potential and associated EET current leads to more negative membrane potential. This EET-induced membrane hyperpolarization is spatially limited to cells in contact with the electrode and within a near-electrode zone (<30 μm) where the hyperpolarization decays with increasing cell-electrode distance. The high spatial and temporal resolution of the reported technique can be used to study the single-cell-level dynamics of EET not only on electrode surfaces, but also during respiration of other solid-phase electron acceptors.

scholarly journals Visualization and Modeling of Inhibition of IL-1β and TNFα mRNA Transcription at the Single-Cell Level

2020 ◽  
Author(s):  
Daniel Kalb ◽  
Huy D. Vo ◽  
Samantha Adikari ◽  
Elizabeth Hong-Geller ◽  
Brian Munsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mrna Expression ◽  
Single Cell ◽  
Inflammatory Responses ◽  
Leukemia Cell ◽  
26S Proteasome ◽  
Leukemia Cell Line ◽  
Single Cell Level ◽  
Cell Level ◽  
Wide Range

AbstractIL-1β and TNFα are canonical immune response mediators that play key regulatory roles in a wide range of inflammatory responses to both chronic and acute conditions. Here we employ an automated microscopy platform for the analysis of messenger RNA (mRNA) expression of IL-1β and TNFα at the single-cell level. The amount of IL-1β and TNFα mRNA expressed in a human monocytic leukemia cell line (THP-1) is visualized and counted using single-molecule fluorescent in-situ hybridization (smFISH) following exposure of the cells to lipopolysaccharide (LPS), an outer-membrane component of Gram-negative bacteria. We show that the small molecule inhibitors MG132 (a 26S proteasome inhibitor used to block NF-κB signaling) and U0126 (a MAPK Kinase inhibitor used to block CCAAT-enhancer-binding proteins C/EBP) successfully block IL-1β and TNFα mRNA expression. Based upon this single-cell mRNA expression data, mathematical models of gene expression indicate that the drugs U0126 and MG132 affect gene activation/deactivation rates between the basal and highly activated states. Models for which the parameters were informed by the action of each drug independently were able to predict the effects of the combined drug treatment. From our data and models, we postulate that IL-1β is activated by both NF-κB and C/EBP, while TNFα is predominantly activated by NF-κB. Our combined single-cell experimental modeling efforts shows the interconnection between these two genes and demonstrates how the single-cell responses, including the distribution shapes, mean expression, and kinetics of gene expression, change with inhibition.

scholarly journals Visualization and modeling of inhibition of IL-1β and TNF-α mRNA transcription at the single-cell level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel Kalb ◽  
Huy D. Vo ◽  
Samantha Adikari ◽  
Elizabeth Hong-Geller ◽  
Brian Munsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mrna Expression ◽  
Single Cell ◽  
Leukemia Cell ◽  
26S Proteasome ◽  
Leukemia Cell Line ◽  
Single Cell Level ◽  
Cell Level ◽  
Tnf Α ◽  
Wide Range

AbstractIL-1β and TNF-α are canonical immune response mediators that play key regulatory roles in a wide range of inflammatory responses to both chronic and acute conditions. Here we employ an automated microscopy platform for the analysis of messenger RNA (mRNA) expression of IL-1β and TNF-α at the single-cell level. The amount of IL-1β and TNF-α mRNA expressed in a human monocytic leukemia cell line (THP-1) is visualized and counted using single-molecule fluorescent in-situ hybridization (smFISH) following exposure of the cells to lipopolysaccharide (LPS), an outer-membrane component of Gram-negative bacteria. We show that the small molecule inhibitors MG132 (a 26S proteasome inhibitor used to block NF-κB signaling) and U0126 (a MAPK Kinase inhibitor used to block CCAAT-enhancer-binding proteins C/EBP) successfully block IL-1β and TNF-α mRNA expression. Based upon this single-cell mRNA expression data, we screened 36 different mathematical models of gene expression, and found two similar models that capture the effects by which the drugs U0126 and MG132 affect the rates at which the genes transition into highly activated states. When their parameters were informed by the action of each drug independently, both models were able to predict the effects of the combined drug treatment. From our data and models, we postulate that IL-1β is activated by both NF-κB and C/EBP, while TNF-α is predominantly activated by NF-κB. Our combined single-cell experimental and modeling efforts show the interconnection between these two genes and demonstrates how the single-cell responses, including the distribution shapes, mean expression, and kinetics of gene expression, change with inhibition.

scholarly journals Single-Cell Electrophysiological Measurements Reveal Bacterial Membrane Potential Dynamics during Extracellular Electron Transfer

2020 ◽  
Author(s):  
Sahand Pirbadian ◽  
Marko S. Chavez ◽  
Mohamed Y. El-Naggar
Keyword(s):  
Electron Transfer ◽  
Membrane Potential ◽  
Single Cell ◽  
Solid Phase ◽  
Electrochemical Techniques ◽  
Model Organisms ◽  
Extracellular Electron Transfer ◽  
Single Cell Level ◽  
Cell Level ◽  
Wide Range

AbstractExtracellular electron transfer (EET) allows microorganisms to gain energy by linking intracellular reactions to external surfaces ranging from natural minerals to the electrodes of bioelectrochemical renewable energy technologies. In the past two decades, electrochemical techniques have been used to investigate EET in a wide range of microbes, with emphasis on dissimilatory metal-reducing bacteria, such as Shewanella oneidensis MR-1, as model organisms. However, due to the typically bulk nature of these techniques, they are unable to reveal the subpopulation variation in EET or link the observed electrochemical currents to energy gain by individual cells, thus overlooking the potentially complex spatial patterns of activity in bioelectrochemical systems. Here, to address these limitations, we use the cell membrane potential as a bioenergetic indicator of EET by S. oneidensis MR-1 cells. Using a fluorescent membrane potential indicator during in vivo single-cell level fluorescence microscopy in a bioelectrochemical reactor, we demonstrate that membrane potential strongly correlates with the electrode potential, produced current, and position of cells relative to the electrodes. The high spatial and temporal resolution of the reported technique can be used to study the single-cell level dynamics of EET not only on electrode surfaces, but also during respiration of other solid-phase electron acceptors.

Maitotoxin-induced cell death cascade in bovine aortic endothelial cells: divalent cation specificity and selectivity

2004 ◽  
Vol 287 (2) ◽  
pp. C345-C356 ◽  
Author(s):  
Brian J. Wisnoskey ◽  
Mark Estacion ◽  
William P. Schilling
Keyword(s):  
Endothelial Cells ◽  
Cell Death ◽  
Single Cell ◽  
Binding Proteins ◽  
Single Cell Level ◽  
Cell Level ◽  
Aortic Endothelial Cells ◽  
Bovine Aortic Endothelial Cells ◽  
Membrane Blebs ◽  
Cell Death Cascade

The maitotoxin (MTX)-induced cell death cascade in bovine aortic endothelial cells (BAECs), a model for Ca2+ overload-induced toxicity, reflects three sequential changes in plasmalemmal permeability. MTX initially activates Ca2+-permeable, nonselective cation channels (CaNSC) and causes a massive increase in cytosolic free Ca2+ concentration ([Ca2+]i). This is followed by the opening of large endogenous cytolytic/oncotic pores (COP) that allow molecules <800 Da to enter the cell. The cells then lyse not by rupture of the plasmalemma but through the activation of a “death” channel that lets large proteins (e.g., 140–160 kDa) leave the cell. These changes in permeability are accompanied by the formation of membrane blebs. In this study, we took advantage of the well-known differences in affinity of various Ca2+-binding proteins for Ca2+ and Sr2+ vs. Ba2+ to probe their involvement in each phase of the cell death cascade. Using fluorescence techniques at the cell population level (cuvette-based) and at the single-cell level (time-lapse videomicroscopy), we found that the replacement of Ca2+ with either Sr2+ or Ba2+ delayed both MTX-induced activation of COP, as indicated by the uptake of ethidium bromide, and subsequent cell lysis, as indicated by the uptake of propidium iodide or the release of cell-associated green fluorescent protein. MTX-induced responses were mimicked by ionomycin and were significantly delayed in BAPTA-loaded cells. Experiments at the single-cell level revealed that Ba2+ not only delayed the time to cell lysis but also caused desynchronization of the lytic phase. Last, membrane blebs, which were numerous and spherical in Ca2+-containing solutions, were poorly defined and greatly reduced in number in the presence of Ba2+. Taken together, these results suggest that intracellular high-affinity Ca2+-binding proteins are involved in the MTX-induced changes in plasmalemmal permeability that are responsible for cell demise.

scholarly journals Decoding mitochondrial heterogeneity in single muscle fibres by imaging mass cytometry

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Charlotte Warren ◽  
David McDonald ◽  
Roderick Capaldi ◽  
David Deehan ◽  
Robert W. Taylor ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Oxidative Phosphorylation ◽  
Single Cell ◽  
Mitochondrial Disease ◽  
Muscle Fibres ◽  
Single Muscle ◽  
Single Cell Level ◽  
Mass Cytometry ◽  
Cell Level ◽  
Wide Range

Abstract The study of skeletal muscle continues to support the accurate diagnosis of mitochondrial disease and remains important in delineating molecular disease mechanisms. The heterogeneous expression of oxidative phosphorylation proteins and resulting respiratory deficiency are both characteristic findings in mitochondrial disease, hence the rigorous assessment of these at a single cell level is incredibly powerful. Currently, the number of proteins that can be assessed in individual fibres from a single section by immunohistochemistry is limited but imaging mass cytometry (IMC) enables the quantification of further, discrete proteins in individual cells. We have developed a novel workflow and bespoke analysis for applying IMC in skeletal muscle biopsies from patients with genetically-characterised mitochondrial disease, investigating the distribution of nine mitochondrial proteins in thousands of single muscle fibres. Using a semi-automated analysis pipeline, we demonstrate the accurate quantification of protein levels using IMC, providing an accurate measure of oxidative phosphorylation deficiency for complexes I–V at the single cell level. We demonstrate signatures of oxidative phosphorylation deficiency for common mtDNA variants and nuclear-encoded complex I variants and a compensatory upregulation of unaffected oxidative phosphorylation components. This technique can now be universally applied to evaluate a wide range of skeletal muscle disorders and protein targets.

Cytoplasmic dynein

2011 ◽  
Vol 39 (5) ◽  
pp. 1169-1178 ◽  
Author(s):  
Victoria J. Allan
Keyword(s):  
Single Cell ◽  
Recent Progress ◽  
Motor Proteins ◽  
Molecular Motor ◽  
Cytoplasmic Dynein ◽  
Eukaryotic Cells ◽  
Single Cell Level ◽  
Cell Level ◽  
Wide Range ◽  
And Function

The organization and function of eukaryotic cells rely on the action of many different molecular motor proteins. Cytoplasmic dynein drives the movement of a wide range of cargoes towards the minus ends of microtubules, and these events are needed, not just at the single-cell level, but are vital for correct development. In the present paper, I review recent progress on understanding dynein's mechanochemistry, how it is regulated and how it binds to such a plethora of cargoes. The importance of a number of accessory factors in these processes is discussed.

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