scholarly journals Quantitative insights into age-associated DNA-repair inefficiency in single cells

2019 ◽  
Author(s):  
Thomas Z. Young ◽  
Ping Liu ◽  
Murat Acar
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Strand Break ◽  
Cellular Aging ◽  
Dsb Repair ◽  
Phase Duration ◽  
Age Related ◽  
Repair Efficiency ◽  
Single Strand Annealing ◽  
The Impact

ABSTRACTThe double strand break (DSB) is a highly toxic form of DNA damage that is thought to be both a driver and consequence of age-related dysfunction. Although DSB repair is essential for a cell’s survival, little is known about how DSB repair mechanisms are affected by cellular age. Here we characterize the impact of cellular aging on the efficiency of single-strand annealing (SSA), a repair mechanism for DSBs occurring between direct repeats. Using a single-cell reporter of SSA repair, we measure SSA repair efficiency in young and old cells, and report a 23.4% decline in repair efficiency. This decline is not due to increased usage of non-homologous end joining (NHEJ). Instead, we identify increased G1-phase duration in old cells as a factor responsible for the decreased SSA repair efficiency. We further explore how SSA repair efficiency is affected by sequence heterology and find that heteroduplex rejection remains high in old cells. Our work provides novel quantitative insights into the links between cellular aging and DSB repair efficiency at single-cell resolution in replicatively aging cells.

scholarly journals Machine learning based classification of cells into chronological stages using single-cell transcriptomics

2018 ◽  
Author(s):  
Sumeet Pal Singh ◽  
Sharan Janjuha ◽  
Samata Chaudhuri ◽  
Susanne Reinhardt ◽  
Sevina Dietz ◽  
...  
Keyword(s):  
Machine Learning ◽  
Single Cell ◽  
Predictive Power ◽  
Single Cells ◽  
Premature Aging ◽  
Calorie Intake ◽  
Learning Framework ◽  
Pancreatic Cells ◽  
Age Related ◽  
The Impact

ABSTRACTAge-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular age are limited, as they rely on a limited set of histological markers and lack predictive power. Here, we implement GERAS (GEnetic Reference for Age of Single-cell), a machine learning based framework capable of assigning individual cells to chronological stages based on their trans criptomes. GERAS displays greater than 90% accuracy in classifying the chronological stage of zebrafish and human pancreatic cells. The framework demonstrates robustness against biological and technical noise, as evaluated by its performance on independent samplings of single-cells. Additionally, GERAS determines the impact of differences in calorie intake and BMI on the aging of zebrafish and human pancreatic cells, respectively. We further harness the predictive power of GERAS to identify genome-wide molecular factors that correlate with aging. We show that one of these factors, junb, is necessary to maintain the proliferative state of juvenile beta-cells. Our results showcase the applicability of a machine learning framework to classify the chronological stage of heterogeneous cell populations, while enabling to detect pro-aging factors and candidate genes associated with aging.

scholarly journals Rad51-Independent Interchromosomal Double-Strand Break Repair by Gene Conversion Requires Rad52 but Not Rad55, Rad57, or Dmc1

2007 ◽  
Vol 28 (3) ◽  
pp. 897-906 ◽  
Author(s):  
Thomas J. Pohl ◽  
Jac A. Nickoloff
Keyword(s):  
Gene Conversion ◽  
Strand Break ◽  
Double Strand Break ◽  
Single Strand ◽  
Homology Search ◽  
Wild Type ◽  
Dsb Repair ◽  
Single Strand Annealing ◽  
In The Wild ◽  
Break Induced Replication

ABSTRACT Homologous recombination (HR) is critical for DNA double-strand break (DSB) repair and genome stabilization. In yeast, HR is catalyzed by the Rad51 strand transferase and its “mediators,” including the Rad52 single-strand DNA-annealing protein, two Rad51 paralogs (Rad55 and Rad57), and Rad54. A Rad51 homolog, Dmc1, is important for meiotic HR. In wild-type cells, most DSB repair results in gene conversion, a conservative HR outcome. Because Rad51 plays a central role in the homology search and strand invasion steps, DSBs either are not repaired or are repaired by nonconservative single-strand annealing or break-induced replication mechanisms in rad51Δ mutants. Although DSB repair by gene conversion in the absence of Rad51 has been reported for ectopic HR events (e.g., inverted repeats or between plasmids), Rad51 has been thought to be essential for DSB repair by conservative interchromosomal (allelic) gene conversion. Here, we demonstrate that DSBs stimulate gene conversion between homologous chromosomes (allelic conversion) by >30-fold in a rad51Δ mutant. We show that Rad51-independent allelic conversion and break-induced replication occur independently of Rad55, Rad57, and Dmc1 but require Rad52. Unlike DSB-induced events, spontaneous allelic conversion was detected in both rad51Δ and rad52Δ mutants, but not in a rad51Δ rad52Δ double mutant. The frequencies of crossovers associated with DSB-induced gene conversion were similar in the wild type and the rad51Δ mutant, but discontinuous conversion tracts were fivefold more frequent and tract lengths were more widely distributed in the rad51Δ mutant, indicating that heteroduplex DNA has an altered structure, or is processed differently, in the absence of Rad51.

scholarly journals Actin-Related Protein 6 (Arp6) Influences Double-Strand Break Repair in Yeast

2021 ◽  
Vol 1 (2) ◽  
pp. 225-238
Author(s):  
Mohsen Hooshyar ◽  
Daniel Burnside ◽  
Maryam Hajikarimlou ◽  
Katayoun Omidi ◽  
Alexander Jesso ◽  
...  
Keyword(s):  
Dna Damage ◽  
Chromatin Remodeling ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Strand Break ◽  
Dna Double Strand Breaks ◽  
Dsb Repair ◽  
Dna Damaging Agents ◽  
Repair Efficiency ◽  
Chromosomal Breaks

DNA double-strand breaks (DSBs) are the most deleterious form of DNA damage and are repaired through non-homologous end-joining (NHEJ) or homologous recombination (HR). Repair initiation, regulation and communication with signaling pathways require several histone-modifying and chromatin-remodeling complexes. In budding yeast, this involves three primary complexes: INO80-C, which is primarily associated with HR, SWR1-C, which promotes NHEJ, and RSC-C, which is involved in both pathways as well as the general DNA damage response. Here we identify ARP6 as a factor involved in DSB repair through an RSC-C-related pathway. The loss of ARP6 significantly reduces the NHEJ repair efficiency of linearized plasmids with cohesive ends, impairs the repair of chromosomal breaks, and sensitizes cells to DNA-damaging agents. Genetic interaction analysis indicates that ARP6, MRE11 and RSC-C function within the same pathway, and the overexpression of ARP6 rescues rsc2∆ and mre11∆ sensitivity to DNA-damaging agents. Double mutants of ARP6, and members of the INO80 and SWR1 complexes, cause a significant reduction in repair efficiency, suggesting that ARP6 functions independently of SWR1-C and INO80-C. These findings support a novel role for ARP6 in DSB repair that is independent of the SWR1 chromatin remodeling complex, through an apparent RSC-C and MRE11-associated DNA repair pathway.

scholarly journals Morphodynamic signatures of MDA-MB-231 single cells and cell doublets undergoing invasion in confined microenvironments

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xingjian Zhang ◽  
Trevor Chan ◽  
Michael Mak
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Leading Edge ◽  
Cell Group ◽  
Collective State ◽  
Long Term Effects ◽  
Cell Metastasis ◽  
Geometric Confinement ◽  
Short And Long Term ◽  
The Impact

AbstractCancer cell metastasis is a major factor in cancer-related mortality. During the process of metastasis, cancer cells exhibit migratory phenotypes and invade through pores in the dense extracellular matrix. However, the characterization of morphological and subcellular features of cells in similar migratory phenotypes and the effects of geometric confinement on cell morphodynamics are not well understood. Here, we investigate the phenotypes of highly aggressive MDA-MB-231 cells in single cell and cell doublet (an initial and simplified collective state) forms in confined microenvironments. We group phenotypically similar single cells and cell doublets and characterize related morphological and subcellular features. We further detect two distinct migratory phenotypes, fluctuating and non-fluctuating, within the fast migrating single cell group. In addition, we demonstrate an increase in the number of protrusions formed at the leading edge of cells after invasion through geometric confinement. Finally, we track the short and long term effects of varied degrees of confinement on protrusion formation. Overall, our findings elucidate the underlying morphological and subcellular features associated with different single cell and cell doublet phenotypes and the impact of invasion through confined geometry on cell behavior.

scholarly journals Quality assessment of single-cell RNA sequencing data by coverage skewness analysis

2019 ◽  
Author(s):  
Imad Abugessaisa ◽  
Shuhei Noguchi ◽  
Melissa Cardon ◽  
Akira Hasegawa ◽  
Kazuhide Watanabe ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Assessment Method ◽  
Poor Quality ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Gene Coverage ◽  
The Impact

AbstractAnalysis and interpretation of single-cell RNA-sequencing (scRNA-seq) experiments are compromised by the presence of poor quality cells. For meaningful analyses, such poor quality cells should be excluded to avoid biases and large variation. However, no clear guidelines exist. We introduce SkewC, a novel quality-assessment method to identify poor quality single-cells in scRNA-seq experiments. The method is based on the assessment of gene coverage for each single cell and its skewness as a quality measure. To validate the method, we investigated the impact of poor quality cells on downstream analyses and compared biological differences between typical and poor quality cells. Moreover, we measured the ratio of intergenic expression, suggesting genomic contamination, and foreign organism contamination of single-cell samples. SkewC is tested in 37,993 single-cells generated by 15 scRNA-seq protocols. We envision SkewC as an indispensable QC method to be incorporated into scRNA-seq experiment to preclude the possibility of scRNA-seq data misinterpretation.

Testing of solid oxide cells at high current densities

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
André Weber
Keyword(s):  
Single Cell ◽  
High Performance ◽  
High Efficiency ◽  
Electrochemical Impedance ◽  
Single Cells ◽  
Operating Conditions ◽  
Solid Oxide ◽  
Current Densities ◽  
Cell Testing ◽  
The Impact

Abstract Solid Oxide Cells (SOCs) have gained an increasing interest as electrochemical energy converters due to their high efficiency, fuel flexibility and ability of reversible fuel cell/electrolysis operation. During the development process as well as in quality assurance tests, the performance of single cells and cell stacks is commonly evaluated by means of current/voltage- (CV-) characteristics. Despite of the fact that the measurement of a CV-characteristic seems to be simple compared to more complex, dynamic methods as electrochemical impedance spectroscopy or current interrupt techniques, the resulting performance strongly depends on the test setup and the chosen operating conditions. In this paper, the impact of different single cell testing environments and operating conditions on the CV-characteristic of high performance cells is discussed. The influence of cell size, contacting and current collection, contact pressure, fuel flow rate and composition on the achievable cell performance is presented and limitations arising from the test bed and testing conditions will be pointed out. As today’s high performance cells are capable of delivering current densities of several ampere per cm2 a special emphasis will be laid on single cell testing in this current range.

scholarly journals Dissecting heterogeneous cell populations across drug and disease conditions with PopAlign

2020 ◽  
Vol 117 (46) ◽  
pp. 28784-28794
Author(s):  
Sisi Chen ◽  
Paul Rivaud ◽  
Jong H. Park ◽  
Tiffany Tsou ◽  
Emeric Charles ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Large Scale ◽  
Probabilistic Models ◽  
Single Cells ◽  
Measurement Techniques ◽  
Patient Specific ◽  
Cell Populations ◽  
Cell Measurement ◽  
The Impact

Single-cell measurement techniques can now probe gene expression in heterogeneous cell populations from the human body across a range of environmental and physiological conditions. However, new mathematical and computational methods are required to represent and analyze gene-expression changes that occur in complex mixtures of single cells as they respond to signals, drugs, or disease states. Here, we introduce a mathematical modeling platform, PopAlign, that automatically identifies subpopulations of cells within a heterogeneous mixture and tracks gene-expression and cell-abundance changes across subpopulations by constructing and comparing probabilistic models. Probabilistic models provide a low-error, compressed representation of single-cell data that enables efficient large-scale computations. We apply PopAlign to analyze the impact of 40 different immunomodulatory compounds on a heterogeneous population of donor-derived human immune cells as well as patient-specific disease signatures in multiple myeloma. PopAlign scales to comparisons involving tens to hundreds of samples, enabling large-scale studies of natural and engineered cell populations as they respond to drugs, signals, or physiological change.

scholarly journals BRCA-related ATM-mediated DNA double-strand break repair and ovarian aging

2019 ◽  
Vol 26 (1) ◽  
pp. 43-57 ◽  
Author(s):  
Volkan Turan ◽  
Kutluk Oktay
Keyword(s):  
Clinical Evidence ◽  
Strand Break ◽  
Oocyte Quality ◽  
Repair Pathway ◽  
Dsb Repair ◽  
Ovarian Aging ◽  
Age Related ◽  
Dna Double Strand Break ◽  
Targeted Treatments ◽  
Oocyte Aging

Abstract BACKGROUND Oocyte aging has significant clinical consequences, and yet no treatment exists to address the age-related decline in oocyte quality. The lack of progress in the treatment of oocyte aging is due to the fact that the underlying molecular mechanisms are not sufficiently understood. BRCA1 and 2 are involved in homologous DNA recombination and play essential roles in ataxia telangiectasia mutated (ATM)-mediated DNA double-strand break (DSB) repair. A growing body of laboratory, translational and clinical evidence has emerged within the past decade indicating a role for BRCA function and ATM-mediated DNA DSB repair in ovarian aging. OBJECTIVE AND RATIONALE Although there are several competing or complementary theories, given the growing evidence tying BRCA function and ATM-mediated DNA DSB repair mechanisms in general to ovarian aging, we performed this review encompassing basic, translational and clinical work to assess the current state of knowledge on the topic. A clear understanding of the mechanisms underlying oocyte aging may result in targeted treatments to preserve ovarian reserve and improve oocyte quality. SEARCH METHODS We searched for published articles in the PubMed database containing key words, BRCA, BRCA1, BRCA2, Mutations, Fertility, Ovarian Reserve, Infertility, Mechanisms of Ovarian Aging, Oocyte or Oocyte DNA Repair, in the English-language literature until May 2019. We did not include abstracts or conference proceedings, with the exception of our own. OUTCOMES Laboratory studies provided robust and reproducible evidence that BRCA1 function and ATM-mediated DNA DSB repair, in general, weakens with age in oocytes of multiple species including human. In both women with BRCA mutations and BRCA-mutant mice, primordial follicle numbers are reduced and there is accelerated accumulation of DNA DSBs in oocytes. In general, women with BRCA1 mutations have lower ovarian reserves and experience earlier menopause. Laboratory evidence also supports critical role for BRCA1 and other ATM-mediated DNA DSB repair pathway members in meiotic function. When laboratory, translational and clinical evidence is considered together, BRCA-related ATM-mediated DNA DSB repair function emerges as a likely regulator of ovarian aging. Moreover, DNA damage and repair appear to be key features in chemotherapy-induced ovarian aging. WIDER IMPLICATIONS The existing data suggest that the BRCA-related ATM-mediated DNA repair pathway is a strong candidate to be a regulator of oocyte aging, and the age-related decline of this pathway likely impairs oocyte health. This knowledge may create an opportunity to develop targeted treatments to reverse or prevent physiological or chemotherapy-induced oocyte aging. On the immediate practical side, women with BRCA or similar mutations may need to be specially counselled for fertility preservation.

scholarly journals Computation of Single-Cell Metabolite Distributions Using Mixture Models

2020 ◽  
Vol 8 ◽  
Author(s):  
Mona K. Tonn ◽  
Philipp Thomas ◽  
Mauricio Barahona ◽  
Diego A. Oyarzún
Keyword(s):  
Single Cell ◽  
Mixture Models ◽  
Single Cells ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Stochastic Simulations ◽  
Deterministic Models ◽  
Metabolic Heterogeneity ◽  
Cell Expression ◽  
The Impact

Metabolic heterogeneity is widely recognized as the next challenge in our understanding of non-genetic variation. A growing body of evidence suggests that metabolic heterogeneity may result from the inherent stochasticity of intracellular events. However, metabolism has been traditionally viewed as a purely deterministic process, on the basis that highly abundant metabolites tend to filter out stochastic phenomena. Here we bridge this gap with a general method for prediction of metabolite distributions across single cells. By exploiting the separation of time scales between enzyme expression and enzyme kinetics, our method produces estimates for metabolite distributions without the lengthy stochastic simulations that would be typically required for large metabolic models. The metabolite distributions take the form of Gaussian mixture models that are directly computable from single-cell expression data and standard deterministic models for metabolic pathways. The proposed mixture models provide a systematic method to predict the impact of biochemical parameters on metabolite distributions. Our method lays the groundwork for identifying the molecular processes that shape metabolic heterogeneity and its functional implications in disease.

scholarly journals Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART

2017 ◽  
Vol 114 (18) ◽  
pp. E3659-E3668 ◽  
Author(s):  
Ann Wiegand ◽  
Jonathan Spindler ◽  
Feiyu F. Hong ◽  
Wei Shao ◽  
Joshua C. Cyktor ◽  
...  
Keyword(s):  
Single Cell ◽  
Mononuclear Cells ◽  
Single Cells ◽  
Constitutive Expression ◽  
Multiple Time ◽  
Hiv Rna ◽  
Infected Cells ◽  
The Impact ◽  
Hiv 1

Little is known about the fraction of human immunodeficiency virus type 1 (HIV-1) proviruses that express unspliced viral RNA in vivo or about the levels of HIV RNA expression within single infected cells. We developed a sensitive cell-associated HIV RNA and DNA single-genome sequencing (CARD-SGS) method to investigate fractional proviral expression of HIV RNA (1.3-kb fragment of p6, protease, and reverse transcriptase) and the levels of HIV RNA in single HIV-infected cells from blood samples obtained from individuals with viremia or individuals on long-term suppressive antiretroviral therapy (ART). Spiking experiments show that the CARD-SGS method can detect a single cell expressing HIV RNA. Applying CARD-SGS to blood mononuclear cells in six samples from four HIV-infected donors (one with viremia and not on ART and three with viremia suppressed on ART) revealed that an average of 7% of proviruses (range: 2–18%) expressed HIV RNA. Levels of expression varied from one to 62 HIV RNA molecules per cell (median of 1). CARD-SGS also revealed the frequent expression of identical HIV RNA sequences across multiple single cells and across multiple time points in donors on suppressive ART consistent with constitutive expression of HIV RNA in infected cell clones. Defective proviruses were found to express HIV RNA at levels similar to those proviruses that had no obvious defects. CARD-SGS is a useful tool to characterize fractional proviral expression in single infected cells that persist despite ART and to assess the impact of experimental interventions on proviral populations and their expression.

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