Identifying stochastic biochemical networks from single-cell population experiments: A comparison of approaches based on the Fisher information

2013 ◽  
Author(s):  
Jakob Ruess ◽  
John Lygeros
Keyword(s):  
Single Cell ◽  
Cell Population ◽  
Fisher Information ◽  
Biochemical Networks

scholarly journals Resolution of DNA damage at the single-cell level shows largely different actions of X-rays and bleomycin.

1995 ◽  
Vol 43 (2) ◽  
pp. 229-235 ◽  
Author(s):  
M I Affentranger ◽  
W Burkart
Keyword(s):  
Single Cell ◽  
Cell Population ◽  
Large Cell ◽  
Dna Strand Breaks ◽  
Single Cell Level ◽  
X Rays ◽  
Cell Level ◽  
Strand Breaks ◽  
Two Agents ◽  
Dna Strand

Both X-rays and the radiomimetic agent bleomycin (BLM) induce DNA strand breaks, predominantly via reactive radicals. To compare the induction of breaks with the two agents in Chinese hamster (CHO-K1) cells, two different alkaline unwinding methods, a 3H tracer-based analysis of large cell populations and an optical adaption allowing measurement of single cells, were applied. Radiation and BLM show qualitatively similar dose responses when the average number of DNA strand breaks is measured in a large cell population. However, the breakage pattern at the single-cell level indicates large discrepancies between the actions of the two agents. Irradiated cells show a uniform distribution of DNA strand breaks over the cell population. Effects of treatment with 30 micrograms x ml-1 BLM for 2 hr vary from practically zero in some cells to high levels of DNA strand breakage in others. Unlike the repair of radiation-induced DNA breaks, the repair efficiency of BLM-induced DNA strand breaks, as measured at the single-cell level, varies strongly among cells of the same population. Such heterogeneity at the cellular level potentially reduces BLM's usefulness for tumor therapy because the appearance of BLM-resistant subpopulations may critically impair treatment outcome.

scholarly journals Diversity in ATP concentrations in a single bacterial cell population revealed by quantitative single-cell imaging

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Hideyuki Yaginuma ◽  
Shinnosuke Kawai ◽  
Kazuhito V. Tabata ◽  
Keisuke Tomiyama ◽  
Akira Kakizuka ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Population ◽  
Bacterial Cell ◽  
Cell Imaging ◽  
Single Cell Imaging

scholarly journals IKAP - Identifying K mAjor cell Population groups in single-cell RNA-seq analysis

2019 ◽  
Author(s):  
Yun-Ching Chen ◽  
Abhilash Suresh ◽  
Chingiz Underbayev ◽  
Clare Sun ◽  
Komudi Singh ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Population ◽  
Cell Types ◽  
Marker Genes ◽  
Rna Seq ◽  
Population Groups ◽  
Tuning Parameters ◽  
Multiple Datasets ◽  
Cell Groups ◽  
Cell Ontology

AbstractIn single-cell RNA-seq analysis, clustering cells into groups and differentiating cell groups by marker genes are two separate steps for investigating cell identity. However, results in clustering greatly affect the ability to differentiate between cell groups. We develop IKAP – an algorithm identifying major cell groups that improves differentiating by tuning parameters for clustering. Using multiple datasets, we demonstrate IKAP improves identification of major cell types and facilitates cell ontology curation.

scholarly journals Assessment of Heterogeneity of Cytochrome P450 Activity in Cancer-Cell Population by Cytometry of Reaction Rate Constant is Robust to Variation in Substrate Concentration

2020 ◽  
Author(s):  
Mariana Bleker de Oliveira ◽  
Vasilij Koshkin ◽  
Christopher G. R. Perry ◽  
Sergey N. Krylov
Keyword(s):  
Cytochrome P450 ◽  
Single Cell ◽  
Cell Population ◽  
Rate Constant ◽  
Substrate Concentration ◽  
Reaction Rate ◽  
Reaction Rate Constant ◽  
Single Cell Level ◽  
Cell Level ◽  
Key Players

ABSTRACTEnzymes of the cytochrome P450 (CYP) family catalyze the metabolism of chemotherapeutic agents and are among the key players in primary and acquired chemoresistance of cancer. The activity of CYP is heterogeneous in tumor tissues, and the quantitative characteristics of this heterogeneity can be used to predict chemoresistance. Cytometry of reaction rate constant (CRRC) is a kinetic approach to assess cell population heterogeneity by measuring rates of processes at the single-cell level via time-lapse imaging. CRRC was shown to be an accurate and robust method for assessing the heterogeneity of drug-extrusion activity catalyzed by ABC transporters, which are also key players in cancer chemoresistance. We hypothesized that CRRC is also a reliable method for assessing the heterogeneity of CYP activity. Here, we evaluated the robustness of assessing the heterogeneity of CYP activity by CRRC with respect to controlled variation in the concentration of a CYP substrate by comparing CRRC with non-kinetic approaches. We found that changing the substrate concentration by 20% resulted only in minimal changes in the position, width, and asymmetry of the peak in the CRRC histogram, while these parameters varied greatly in the non-kinetic histograms. Moreover, the Kolmogorov-Smirnov statistical test showed that the distribution of the cell population in CRRC histograms was not significantly different; the result was opposite for non-kinetic histograms. In conclusion, we were able to demonstrate the robustness of CRRC with respect to changes in substrate concentration when evaluating CYP activity at the single-cell level.

scholarly journals Spatiotemporal transcriptome at single-cell resolution reveals key radial glial cell population in axolotl telencephalon development and regeneration

2021 ◽  
Author(s):  
Xiaoyu Wei ◽  
Sulei Fu ◽  
Hanbo Li ◽  
Yang Liu ◽  
Shuai Wang ◽  
...  
Keyword(s):  
Single Cell ◽  
Glial Cell ◽  
Cell Population ◽  
Cell Types ◽  
Mammalian Brain ◽  
Regeneration Ability ◽  
Radial Glial Cell ◽  
Cell Dynamics ◽  
Brain Regeneration ◽  
Radial Glial

Brain regeneration requires a precise coordination of complex responses in a time- and region-specific manner. Identifying key cell types and molecules that direct brain regeneration would provide potential targets for the advance of regenerative medicine. However, progress in the field has been hampered largely due to very limited regeneration capacity of the mammalian brain and understanding of the regeneration process at both cellular and molecular level. Here, using axolotl brain with astonishing regeneration ability upon injury, and the Stereo-seq (SpaTial Enhanced REsolution Omics-sequencing), we reconstruct the first architecture of axolotl telencephalon with gene expression profiling at single-cell resolution, and fine cell dynamics maps throughout development and regeneration. Intriguingly, we discover a marked heterogeneity of radial glial cell (RGC) types with distinct behaviors. Of note, one subtype of RGCs is activated since early regeneration stages and proliferates while other RGCs remain dormant. Such RGC subtype appears to be the major cell population involved in early wound healing response and gradually covers the injured area before presumably transformed into the lost neurons. Altogether, our work systematically decodes the complex cellular and molecular dynamics of axolotl telencephalon in development and regeneration, laying the foundation for studying the regulatory mechanism of brain regeneration in future.

Local progenitor cells shape the neoplastic vasculature and promote brain tumor growth.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14044-e14044
Author(s):  
Roland Kälin ◽  
Linzhi Cai ◽  
Dongxu Zhao ◽  
Huabin Zhang ◽  
Wenlong Zhang ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Single Cell ◽  
Progenitor Cells ◽  
Cell Population ◽  
Expression Profile ◽  
Progenitor Cell ◽  
Myeloid Cells ◽  
Lineage Tracing

e14044 Background: Aggressive brain tumors like glioblastoma depend on support by their local environment. While the role of tumor-associated myeloid cells on glioblastoma progression is well-documented, we have only partial knowledge of the pathological impact of glioblastoma -parenchymal progenitor cells. Methods: We investigated the glioblastoma microenvironment with transgenic lineage-tracing models ( nestin-creER2, R26-tdTomato and sox2-creER2,R26-tdTomato), intravital imaging, single-cell transcriptomics, immunofluorescence and flow-cytometry as well as histopathology and characterized a previously unknown tumor-associated progenitor cell. In functional experiments, we studied the knockout of the transcription factor SOX2 in these tumor-associated cells. Results: Lineage-traced cells from mouse glioblastoma were obtained by flow-cytometry and single cell transcriptomes compared to established gene expression data from brain tumor parenchymal cells. The traced tumor-associated cells had a transcriptomic profile largely resembling myeloid cells and expressed microglia-/macrophage-markers on the protein-level. However, transgenic models and bone-marrow chimera revealed that the traced cells were clearly distinct from microglia or macrophages. The traced tumor associated cells with a myeloid expression profile derived from a SOX2-dependent progenitor cell. Consequently, conditional Sox2-knockout ablated the entire myeloid-like cell population. Remarkably, this tumor-associated cell population had a large impact on disease-progression causing significant reduction of glioblastoma –vascularization to 53%, changing vascular function and leading to a decrease in tumor volume to 42% as compared to controls. The myeloid-like progenitor cells were identified in human brain tumors by immunofluorescence and in scRNA-seq data. Conclusions: We identified a previously unacknowledged population of tumor-associated progenitor cells with a myeloid-like expression profile that transiently appeared during glioblastoma growth. These progenitors have strong impact on glioblastoma progression and point towards a new and promising therapeutic target in order to support anti-angiogenic regimen in glioblastoma.

Mapping single-cell-resolution cell phylogeny reveals cell population dynamics during organ development

2021 ◽  
Vol 18 (12) ◽  
pp. 1506-1514
Author(s):  
Kehui Liu ◽  
Shanjun Deng ◽  
Chang Ye ◽  
Zeqi Yao ◽  
Jianguo Wang ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Single Cell ◽  
Cell Population ◽  
Organ Development ◽  
Cell Population Dynamics ◽  
Resolution Cell

scholarly journals Quantitative assessment of cell population diversity in single-cell landscapes

PLoS Biology ◽  
2018 ◽  
Vol 16 (10) ◽  
pp. e2006687 ◽  
Author(s):  
Qi Liu ◽  
Charles A. Herring ◽  
Quanhu Sheng ◽  
Jie Ping ◽  
Alan J. Simmons ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Population ◽  
Quantitative Assessment ◽  
Population Diversity

ON SIMULATING THE GENERATION OF MOSAICISM DURING MAMMALIAN CEREBRAL CORTICAL DEVELOPMENT

2009 ◽  
Vol 17 (01) ◽  
pp. 27-62 ◽  
Author(s):  
MICHAEL A. CASE ◽  
HUGH R. MACMILLAN
Keyword(s):  
Decision Making ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Population ◽  
Cellular Response ◽  
Molecular Mechanisms ◽  
Cortical Development ◽  
Coarse Grained ◽  
Biological Organization ◽  
Cellular Processes

Renewed calls for a systems biology reflect the hope hat enduring biological questions at single-cell and cell-population scales will be resolved as modern molecular biology, with its reductionist program, approaches a nearly-complete characterization of the molecular mechanisms of specific cellular processes. Due to the confounding complexity of biological organization across these scales, computational science is sought to complement the intuition of experimentalists. However, with respect to the molecular basis of cellular processes during development and disease, a gulf between feasible simulations and realistic biology persists. Formidable are the mathematical and computational challenges to conducting and validating cell population-scale simulations, drawn from single-cell level and molecular level details. Nonetheless, in some biological contexts, a focus on core processes crafted by evolution can yield coarse-grained mathematical models that retain explanatory potential despite drastic simplification of known biochemical kinetics. In this article, we bring this modeling philosophy to bear on the nature of neural progenitor cell decision making during mammalian cerebral cortical development. Specifically, we present the computational component to a research program addressing developmental links between (i) the cellular response to endogenous DNA damage, (ii) primary mechanisms of neuronal genetic heterogeneity, or mosaicism, and (iii) the cell fate decision making that defines the population kinetics of neurogenesis.

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