scholarly journals Stable heteroplasmy at the single cell level is facilitated by inter-cellular exchange of mtDNA

2014 ◽  
Author(s):  
Anitha D Jayaprakash ◽  
Erica Benson ◽  
Swapna Gone ◽  
Raymond Liang ◽  
Jaehee Shim ◽  
...  
Keyword(s):  
Cell Lines ◽  
Rare Variants ◽  
Single Cells ◽  
Cell Level ◽  
Daughter Cells ◽  
Mtdna Haplotypes ◽  
A Cell ◽  
Multiple Cell ◽  
Total Dna ◽  
The Stability

Eukaryotic cells carry two genomes, nuclear (nDNA) and mitochondrial (mtDNA), which are ostensibly decoupled in their replication, segregation and inheritance. It is increasingly appreciated that heteroplasmy, the occurrence of multiple mtDNA haplotypes in a cell, plays an important biological role, but its features are not well understood. Accurately determining the diversity of mtDNA has been difficult, due to the relatively small amount of mtDNA in each cell (< 1% of the total DNA), the intercellular variability of mtDNA content and mtDNA pseudogenes (Numts) in nDNA. To understand the nature of heteroplasmy, we developed Mseek, a novel technique to purify and sequence mtDNA. Mseek yields high purity (> 90%) mtDNA and its ability to detect rare variants is limited only by sequencing depth, providing unprecedented sensitivity and specificity. Using Mseek, we confirmed the ubiquity of heteroplasmy by analyzing mtDNA from a diverse set of cell lines and human samples. Applying Mseek to colonies derived from single cells, we find heteroplasmy is stably maintained in individual daughter cells over multiple cell divisions. We hypothesized that the stability of heteroplasmy could be facilitated by inter-cellular exchange of mtDNA. We explicitly demonstrate this exchange by co-culturing cell lines with distinct mtDNA haplotypes. Our results shed new light on the maintenance of heteroplasmy and provide a novel platform to investigate features of heteroplasmy in normal and diseased states.

scholarly journals Heterogeneity and Intrinsic Variation in Spatial Genome Organization

2017 ◽  
Author(s):  
Elizabeth H. Finn ◽  
Gianluca Pegoraro ◽  
Hugo B. Brandão ◽  
Anne-Laure Valton ◽  
Marlies E. Oomen ◽  
...  
Keyword(s):  
Genome Organization ◽  
Single Cells ◽  
Human Fibroblasts ◽  
Intrinsic Variability ◽  
Cell Level ◽  
3D Genome ◽  
3D Space ◽  
A Cell ◽  
Spatial Genome Organization ◽  
Independent Behavior

AbstractThe genome is hierarchically organized in 3D space and its architecture is altered in differentiation, development and disease. Some of the general principles that determine global 3D genome organization have been established. However, the extent and nature of cell-to-cell and cell-intrinsic variability in genome architecture are poorly characterized. Here, we systematically probe the heterogeneity in genome organization in human fibroblasts by combining high-resolution Hi-C datasets and high-throughput genome imaging. Optical mapping of several hundred genome interaction pairs at the single cell level demonstrates low steady-state frequencies of colocalization in the population and independent behavior of individual alleles in single nuclei. Association frequencies are determined by genomic distance, higher-order chromatin architecture and chromatin environment. These observations reveal extensive variability and heterogeneity in genome organization at the level of single cells and alleles and they demonstrate the coexistence of a broad spectrum of chromatin and genome conformations in a cell population.

The evolution of multicellularity and cancer: views and paradigms

2020 ◽  
Vol 48 (4) ◽  
pp. 1505-1518
Author(s):  
Aurora M. Nedelcu
Keyword(s):  
Single Cells ◽  
Molecular Networks ◽  
Cell Level ◽  
Therapeutic Implications ◽  
Fitness Advantage ◽  
Somatic Evolution ◽  
Unicellular Organisms ◽  
Cooperative Behaviors ◽  
The Stability ◽  
Somatic Selection

Conceptually and mechanistically, the evolution of multicellularity required the integration of single cells into new functionally, reproductively and evolutionary stable multicellular individuals. As part of this process, a change in levels of selection occurred, with selection at the multicellular level overriding selection at the cell level. The stability of multicellular individuals is dependent on a combination of mechanisms that supress within-group evolution, by both reducing the occurrence of somatic mutations as well as supressing somatic selection. Nevertheless, mutations that, in a particular microenvironment, confer mutant lineages a fitness advantage relative to normal somatic cells do occur, and can result in cancer. This minireview highlights several views and paradigms that relate the evolution of multicellularity to cancer. As a phenomenon, cancer is generally understood as a failure of multicellular systems to suppress somatic evolution. However, as a disease, cancer is interpreted in different frameworks: (i) a breakdown of cooperative behaviors underlying the evolution of multicellularity, (ii) a disruption of molecular networks established during the emergence of multicellularity to impose constraints on single-celled units, or (iii) an atavistic state resulting from reactivating primitive programs that originated in the earliest unicellular species. A number of assumptions are common in all the views relating cancer as a disease to the evolution of multicellularity. For instance, cancer is considered a reversal to unicellularity, and cancer cells are thought to both resemble unicellular organisms and benefit from ancestral-like traits. Nevertheless, potential limitations of current paradigms should be acknowledged as different perspectives can provide novel insights with potential therapeutic implications.

scholarly journals Growth and single cell kinetics of the loricate choanoflagellate Diaphanoeca grandis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Niels Thomas Eriksen ◽  
Jakob Tophøj ◽  
Rasmus Dam Wollenberg ◽  
Teis Esben Sondergaard ◽  
Peter Funch ◽  
...  
Keyword(s):  
Cell Division ◽  
Single Cell ◽  
Life Histories ◽  
Daughter Cell ◽  
Cell Kinetics ◽  
Cell Formation ◽  
Daughter Cells ◽  
History Of ◽  
A Cell ◽  
Multiple Cell

Abstract Choanoflagellates are common members of planktonic communities. Some have complex life histories that involve transitions between multiple cell stages. We have grown the loricate choanoflagellate Diaphanoeca grandis on the bacterium Pantoea sp. and integrated kinetic observations at the culture level and at the single cell level. The life history of D. grandis includes a cell division cycle with a number of recognisable cell stages. Mature, loricate D. grandis were immobile and settled on the bottom substratum. Daughter cells were ejected from the lorica 30 min. after cell division, became motile and glided on the bottom substratum until they assembled a lorica. Single cell kinetics could explain overall growth kinetics in D. grandis cultures. The specific growth rate was 0.72 day−1 during exponential growth while mature D. grandis produced daughter cells at a rate of 0.9 day−1. Daughter cells took about 1.2 h to mature. D. grandis was able to abandon and replace its lorica, an event that delayed daughter cell formation by more than 2 days. The frequency of daughter cell formation varied considerably among individuals and single cell kinetics demonstrated an extensive degree of heterogeneity in D. grandis cultures, also when growth appeared to be balanced.

Using FRET to Measure the Time it Takes for a Cell to Destroy a Virus

2019 ◽  
Author(s):  
Candace E. Benjamin ◽  
Zhuo Chen ◽  
Olivia Brohlin ◽  
Hamilton Lee ◽  
Stefanie Boyd ◽  
...  
Keyword(s):  
Cellular Uptake ◽  
Rhodamine B ◽  
Virus Like Particle ◽  
A Cell ◽  
Viral Nanoparticles ◽  
The Stability ◽  
Open Question ◽  
Viral Surface ◽  
Fret Pair

<div><div><div><p>The emergence of viral nanotechnology over the preceding two decades has created a number of intellectually captivating possible translational applications; however, the in vitro fate of the viral nanoparticles in cells remains an open question. Herein, we investigate the stability and lifetime of virus-like particle (VLP) Qβ - a representative and popular VLP for several applications - following cellular uptake. By exploiting the available functional handles on the viral surface, we have orthogonally installed the known FRET pair, FITC and Rhodamine B, to gain insight of the particle’s behavior in vitro. Based on these data, we believe VLPs undergo aggregation in addition to the anticipated proteolysis within a few hours of cellular uptake.</p></div></div></div>

An artificial intelligent platform for live cell identification and the detection of cross-contamination (Preprint)

2019 ◽  
Author(s):  
Ruixin Wang ◽  
Dongni Wang ◽  
Dekai Kang ◽  
Xusen Guo ◽  
Chong Guo ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Cell Morphology ◽  
Single Cell Level ◽  
Cross Contamination ◽  
Cell Level ◽  
Cell Identification ◽  
Pure Cell ◽  
Microscopy Images

BACKGROUND In vitro human cell line models have been widely used for biomedical research to predict clinical response, identify novel mechanisms and drug response. However, one-fifth to one-third of cell lines have been cross-contaminated, which can seriously result in invalidated experimental results, unusable therapeutic products and waste of research funding. Cell line misidentification and cross-contamination may occur at any time, but authenticating cell lines is infrequent performed because the recommended genetic approaches are usually require extensive expertise and may take a few days. Conversely, the observation of live-cell morphology is a direct and real-time technique. OBJECTIVE The purpose of this study was to construct a novel computer vision technology based on deep convolutional neural networks (CNN) for “cell face” recognition. This was aimed to improve cell identification efficiency and reduce the occurrence of cell-line cross contamination. METHODS Unstained optical microscopy images of cell lines were obtained for model training (about 334 thousand patch images), and testing (about 153 thousand patch images). The AI system first trained to recognize the pure cell morphology. In order to find the most appropriate CNN model，we explored the key image features in cell morphology classification tasks using the classical CNN model-Alexnet. After that, a preferred fine-grained recognition model BCNN was used for the cell type identification (seven classifications). Next, we simulated the situation of cell cross-contamination and mixed the cells in pairs at different ratios. The detection of the cross-contamination was divided into two levels, whether the cells are mixed and what the contaminating cell is. The specificity, sensitivity, and accuracy of the model were tested separately by external validation. Finally, the segmentation model DialedNet was used to present the classification results at the single cell level. RESULTS The cell texture and density were the influencing factors that can be better recognized by the bilinear convolutional neural network (BCNN) comparing to AlexNet. The BCNN achieved 99.5% accuracy in identifying seven pure cell lines and 86.3% accuracy for detecting cross-contamination (mixing two of the seven cell lines). DilatedNet was applied to the semantic segment for analyzing in single-cell level and achieved an accuracy of 98.2%. CONCLUSIONS This study successfully demonstrated that cell lines can be morphologically identified using deep learning models. Only light-microscopy images and no reagents are required, enabling most labs to routinely perform cell identification tests.

scholarly journals Leukocytes with chromosome Y loss have reduced abundance of the cell surface immunoprotein CD99

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jonas Mattisson ◽  
Marcus Danielsson ◽  
Maria Hammond ◽  
Hanna Davies ◽  
Caroline J. Gallant ◽  
...  
Keyword(s):  
Cell Surface ◽  
Single Cells ◽  
Surface Protein ◽  
Protein Abundance ◽  
Blood Leukocytes ◽  
Chromosome Y ◽  
Increased Risk ◽  
A Cell ◽  
Pseudoautosomal Regions ◽  
Male Specific

AbstractMosaic loss of chromosome Y (LOY) in immune cells is a male-specific mutation associated with increased risk for morbidity and mortality. The CD99 gene, positioned in the pseudoautosomal regions of chromosomes X and Y, encodes a cell surface protein essential for several key properties of leukocytes and immune system functions. Here we used CITE-seq for simultaneous quantification of CD99 derived mRNA and cell surface CD99 protein abundance in relation to LOY in single cells. The abundance of CD99 molecules was lower on the surfaces of LOY cells compared with cells without this aneuploidy in all six types of leukocytes studied, while the abundance of CD proteins encoded by genes located on autosomal chromosomes were independent from LOY. These results connect LOY in single cells with immune related cellular properties at the protein level, providing mechanistic insight regarding disease vulnerability in men affected with mosaic chromosome Y loss in blood leukocytes.

scholarly journals SUGAR-seq enables simultaneous detection of glycans, epitopes, and the transcriptome in single cells

2021 ◽  
Vol 7 (8) ◽  
pp. eabe3610
Author(s):  
Conor J. Kearney ◽  
Stephin J. Vervoort ◽  
Kelly M. Ramsbottom ◽  
Izabela Todorovski ◽  
Emily J. Lelliott ◽  
...  
Keyword(s):  
Single Cell ◽  
Posttranslational Modification ◽  
Cellular Differentiation ◽  
Single Cells ◽  
Simultaneous Detection ◽  
Surface Protein ◽  
Rna Seq ◽  
Cell Level ◽  
Simultaneous Integration ◽  
Unique Surface

Multimodal single-cell RNA sequencing enables the precise mapping of transcriptional and phenotypic features of cellular differentiation states but does not allow for simultaneous integration of critical posttranslational modification data. Here, we describe SUrface-protein Glycan And RNA-seq (SUGAR-seq), a method that enables detection and analysis of N-linked glycosylation, extracellular epitopes, and the transcriptome at the single-cell level. Integrated SUGAR-seq and glycoproteome analysis identified tumor-infiltrating T cells with unique surface glycan properties that report their epigenetic and functional state.

scholarly journals Combinatorial CRISPR screen identifies fitness effects of gene paralogues

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Nicola A. Thompson ◽  
Marco Ranzani ◽  
Louise van der Weyden ◽  
Vivek Iyer ◽  
Victoria Offord ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Unknown Function ◽  
Single Copy ◽  
Genetic Redundancy ◽  
Synthetic Lethal ◽  
Fitness Effects ◽  
Synthetic Lethal Interactions ◽  
Crispr Screen ◽  
Multiple Cell

AbstractGenetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. Our studies reveal the fitness effects of FAM50A/FAM50B in cancer cells.

scholarly journals Multiplexed profiling of single-cell extracellular vesicles secretion

2019 ◽  
Vol 116 (13) ◽  
pp. 5979-5984 ◽  
Author(s):  
Yahui Ji ◽  
Dongyuan Qi ◽  
Linmei Li ◽  
Haoran Su ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Extracellular Vesicles ◽  
Single Cell Analysis ◽  
Comprehensive Evaluation ◽  
Single Cells ◽  
Deep Understanding ◽  
Principal Component ◽  
Cell Heterogeneity ◽  
Indispensable Tool

Extracellular vesicles (EVs) are important intercellular mediators regulating health and diseases. Conventional methods for EV surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EV secretion. Herein, by using spatially patterned antibody barcodes, we realized multiplexed profiling of single-cell EV secretion from more than 1,000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to a deep understanding of previously undifferentiated single-cell heterogeneity underlying EV secretion. Notably, we observed that the decrement of certain EV phenotypes (e.g.,CD63+EV) was associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EV secretion and cytokines secretion simultaneously from the same single cells to investigate the multidimensional spectrum of cellular communications, from which we resolved tiered functional subgroups with distinct secretion profiles by visualized clustering and principal component analysis. In particular, we found that different cell subgroups dominated EV secretion and cytokine secretion. The technology introduced here enables a comprehensive evaluation of EV secretion heterogeneity at single-cell level, which may become an indispensable tool to complement current single-cell analysis and EV research.

The locomotory behaviour of small groups of fibroblasts

1965 ◽  
Vol 162 (988) ◽  
pp. 289-302 ◽  
Keyword(s):  
Small Groups ◽  
Control Groups ◽  
Isolated Cells ◽  
Daughter Cells ◽  
A Cell ◽  
Locomotory Behaviour ◽  
Chick Embryo Heart ◽  
Embryo Heart ◽  
Random Nature ◽  
Chemotactic Gradient

Small groups of two to four fibroblasts at the periphery of outgrowths from cultured explants of chick embryo heart were isolated from their neighbours by sweeping away the nearby cells. The groups and the explants were left attached to the glass substrate, undisturbed. The behaviour of the isolated cells was photographically recorded during about 8 h of further culture. The cells of these groups dispersed, though not as a rule so far as to lose all mutual contacts, the dispersal being counterbalanced by the addition of new cells through mitosis. The accompanying changes in speed of locomotion, and the non-random nature of the spreading, are interpreted in terms of the effects of contacts between the cells. During the first four hours after isolation, but not thereafter, the cells of the groups on the average moved slowly away from the explant. Control groups in an intact outgrowth moved away faster and with no diminution of speed during the period of observation. The movement of the isolated groups can be partly accounted for by the tendency of cells to conserve for a time the direction of their movement before isolation; and by a strong reluctance of the isolated cells to move across the area, from which cells had been scraped away, that lay between the group and the explant. A new outgrowth of the residual sheet of cells still connected to the explant, however, advanced across this area, approaching and in most cases overhauling the isolated group. It is concluded that a chemotactic gradient around the explant is unlikely to play any significant part in the outward movement of fibroblasts from an explant in tissue culture. The cells of the isolated groups underwent an outburst of mitosis about 3 h after isolation. Mitoses in these relatively free cells are oriented in relation to the polarity of the cell before division. Locomotion of the daughter-cells tends to be faster than usual for at least 2 h after a cell divides.

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