scholarly journals Single-cell analysis reveals selection of TP53-mutated clones after MDM2 inhibition

2022 ◽  
Author(s):  
Nabih Maslah ◽  
Emmanuelle Verger ◽  
Stéphane Giraudier ◽  
Mathias Chea ◽  
Ronald Hoffman ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Selection Process ◽  
Myeloproliferative Neoplasms ◽  
Clonal Evolution ◽  
In Vitro Test ◽  
Tp53 Mutations ◽  
The Impact ◽  
Selection Of

The mechanisms of transformation of chronic myeloproliferative neoplasms (MPN) to leukemia are largely unknown but TP53mutations acquisition is considered a key event in this process. P53 is a main tumor suppressor but mutations in this protein per se do not confer a proliferative advantage to the cells and a selection process is needed for the expansion of mutant clones. MDM2 inhibitors may rescue normal p53 from degradation and have been evaluated in a variety of cancers with promising results. However the impact of these drugs on TP53 mutated cells is underexplored. We report herein evidence of a direct effect of MDM2 inhibition on the selection of MPN patients' cells harboring TP53 mutations. To decipher whether these mutations can arise in a specific molecular context we used a DNA single cell approach to determine the clonal architecture of TP53 mutated cells. We observed that TP53 mutations are late events in MPN mainly occurring in the driver clone while clonal evolution frequently consists of sequential branching instead of linear consecutive acquisition of mutations in the same clone. At the single cell level the presence of additional mutations does not influence the selection of TP53 mutant cells by MDM2 inhibitor treatment. Also, we describe an in vitro test allowing to predict the emergence of TP53 mutated clones. Altogether, this is the first demonstration that a drug treatment can directly favor the emergence of TP53-mutated subclones in MPN.

Fabrication of high-aspect-ratio microstructures in polymer microfluid chips for in vitro single-cell analysis

2016 ◽  
Vol 61 (10) ◽  
pp. 1566-1571 ◽  
Author(s):  
A. S. Bukatin ◽  
I. S. Mukhin ◽  
E. I. Malyshev ◽  
I. V. Kukhtevich ◽  
A. A. Evstrapov ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Single Cell ◽  
High Aspect Ratio ◽  
Single Cell Analysis ◽  
Cell Analysis

scholarly journals Single Cell Analysis Reveals That IL-4 Receptor/Stat6 Signaling Is Not Required for the In Vivo or In Vitro Development of CD4+Lymphocytes with a Th2 Cytokine Profile

2000 ◽  
Vol 164 (6) ◽  
pp. 3047-3055 ◽  
Author(s):  
Dragana Jankovic ◽  
Marika C. Kullberg ◽  
Nancy Noben-Trauth ◽  
Patricia Caspar ◽  
William E. Paul ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Cytokine Profile ◽  
Cell Analysis ◽  
In Vitro Development ◽  
Th2 Cytokine ◽  
Vitro Development ◽  
Cd4 Lymphocytes

scholarly journals Single-cell analysis reveals IGF-1 potentiation of inhibition of the TGF-β/Smad pathway of fibrosis in human keratocytes in vitro

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Tomislav Sarenac ◽  
Martin Trapecar ◽  
Lidija Gradisnik ◽  
Marjan Slak Rupnik ◽  
Dusica Pahor
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Smad Pathway ◽  
Human Keratocytes

scholarly journals Single cell analysis reveals the impact of age and maturation stage on the human oocyte transcriptome

2020 ◽  
Author(s):  
Silvia Llonch ◽  
Montserrat Barragán ◽  
Paula Nieto ◽  
Anna Mallol ◽  
Marc Elosua-Bayes ◽  
...  
Keyword(s):  
Single Cell ◽  
Chromosome Segregation ◽  
Maternal Age ◽  
Maturation Stage ◽  
P Value ◽  
Rna Seq ◽  
Transcript Levels ◽  
Human Oocytes ◽  
The Impact

AbstractStudy questionTo which degree does maternal age affect the transcriptome of human oocytes at the germinal vesicle (GV) stage or at metaphase II after maturation in vitro (IVM-MII)?Summary answerWhile the oocytes’ transcriptome is predominantly determined by maturation stage, transcript levels of genes related to chromosome segregation, mitochondria and RNA processing are affected by age after in vitro maturation of denuded oocytes.What is known alreadyFemale fertility is inversely correlated with maternal age due to both a depletion of the oocyte pool and a reduction in oocyte developmental competence. Few studies have addressed the effect of maternal age on the human mature oocyte (MII) transcriptome, which is established during oocyte growth and maturation, and the pathways involved remain unclear. Here, we characterize and compare the transcriptomes of a large cohort of fully grown GV and IVM-MII oocytes from women of varying reproductive age.Study design, size, durationIn this prospective molecular study, 37 women were recruited from May 2018 to June 2019. The mean age was 28.8 years (SD=7.7, range 18-43). A total of 72 oocytes were included in the study at GV stage after ovarian stimulation, and analyzed as GV (n=40) and in vitro matured oocytes (IVM-MII; n=32).Participants/materials, setting, methodsDenuded oocytes were included either as GV at the time of ovum pick-up or as IVM-MII after in vitro maturation for 30 hours in G2™ medium, and processed for transcriptomic analysis by single-cell RNA-seq using the Smart-seq2 technology. Cluster and maturation stage marker analysis were performed using the Seurat R package. Genes with an average fold change greater than 2 and a p-value < 0.01 were considered maturation stage markers. A Pearson correlation test was used to identify genes whose expression levels changed progressively with age. Those genes presenting a correlation value (R) >= |0.3| and a p-value < 0.05 were considered significant.Main results and the role of chanceFirst, by exploration of the RNA-seq data using tSNE dimensionality reduction, we identified two clusters of cells reflecting the oocyte maturation stage (GV and IVM-MII) with 4,445 and 324 putative marker genes, respectively. Next we identified genes, for which RNA levels either progressively increased or decreased with age. This analysis was performed independently for GV and IVM-MII oocytes. Our results indicate that the transcriptome is more affected by age in IVM-MII oocytes (1,219 genes) than in GV oocytes (596 genes). In particular, we found that genes involved in chromosome segregation and RNA splicing significantly increase in transcript levels with age, while genes related to mitochondrial activity present lower transcript levels with age. Gene regulatory network analysis revealed potential upstream master regulator functions for genes whose transcript levels present positive (GPBP1, RLF, SON, TTF1) or negative (BNC1, THRB) correlation with age.Limitations, reasons for cautionIVM-MII oocytes used in this study were obtained after in vitro maturation of denuded GV oocytes, therefore, their transcriptome might not be fully representative of in vivo matured MII oocytes.The Smart-seq2 methodology used in this study detects polyadenylated transcripts only and we could therefore not assess non-polyadenylated transcripts.Wider implications of the findingsOur analysis suggests that advanced maternal age does not globally affect the oocyte transcriptome at GV or IVM-MII stages. Nonetheless, hundreds of genes displayed altered transcript levels with age, particularly in IVM-MII oocytes. Especially affected by age were genes related to chromosome segregation and mitochondrial function, pathways known to be involved in oocyte ageing. Our study thereby suggests that misregulation of chromosome segregation and mitochondrial pathways also at the RNA-level might contribute to the age-related quality decline in human oocytes.Study funding/competing interest(s)This study was funded by the AXA research fund, the European commission, intramural funding of Clinica EUGIN, the Spanish Ministry of Science, Innovation and Universities, the Catalan Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) and by contributions of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership and to the “Centro de Excelencia Severo Ochoa”.The authors have no conflict of interest to declare.

scholarly journals Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hongyu Zhao ◽  
Yu Teng ◽  
Wende Hao ◽  
Jie Li ◽  
Zhefeng Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Single Cell ◽  
Cancer Progression ◽  
Cox Regression ◽  
Single Cell Analysis ◽  
Cell Types ◽  
In Vitro Assays ◽  
Migration And Invasion ◽  
Dominant Type

Abstract Background Ovarian cancer was one of the leading causes of female deaths. Patients with OC were essentially incurable and portends a poor prognosis, presumably because of profound genetic heterogeneity limiting reproducible prognostic classifications. Methods We comprehensively analyzed an ovarian cancer single-cell RNA sequencing dataset, GSE118828, and identified nine major cell types. Relationship between the clusters was explored with CellPhoneDB. A malignant epithelial cluster was confirmed using pseudotime analysis, CNV and GSVA. Furthermore, we constructed the prediction model (i.e., RiskScore) consisted of 10 prognosis-specific genes from 2397 malignant epithelial genes using the LASSO Cox regression algorithm based on public datasets. Then, the prognostic value of Riskscore was assessed with Kaplan–Meier survival analysis and time-dependent ROC curves. At last, a series of in-vitro assays were conducted to explore the roles of IL4I1, an important gene in Riskscore, in OC progression. Results We found that macrophages possessed the most interaction pairs with other clusters, and M2-like TAMs were the dominant type of macrophages. C0 was identified as the malignant epithelial cluster. Patients with a lower RiskScore had a greater OS (log-rank P < 0.01). In training set, the AUC of RiskScore was 0.666, 0.743 and 0.809 in 1-year, 3-year and 5-year survival, respectively. This was also validated in another two cohorts. Moreover, downregulation of IL4I1 inhibited OC cells proliferation, migration and invasion. Conclusions Our work provide novel insights into our understanding of the heterogeneity among OCs, and would help elucidate the biology of OC and provide clinical guidance in prognosis for OC patients.

scholarly journals HIV-1 provirus transcription and translation in macrophages differs from pre-integrated cDNA complexes and requires E2F transcriptional programs

2021 ◽  
Author(s):  
Albebson L. Lim ◽  
Philip Moos ◽  
Christopher D. Pond ◽  
Erica C. Larson ◽  
Laura J. Martins ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Immunological Response ◽  
Virus Production ◽  
Cell Analysis ◽  
Gene Transcripts ◽  
Nuanced Understanding ◽  
New Perspective ◽  
Hiv 1

AbstractHIV-1 cDNA pre-integration complexes have been shown to persist for weeks in macrophages and to be transcriptionally active. Early and late gene transcripts are produced, along with some viral proteins, yet whole virus is not. While previous work has focused on the transcription and translation of HIV-1 genes; our understanding of cellular milieu that accompanies viral production is incomplete. We have used an in vitro system to model HIV-1 infection of macrophages, and single cell RNA sequencing (scRNA-seq) to compare the transcriptomes of uninfected cells, cells harboring pre-integration HIV-1 complexes (PIC) and those containing integrated provirus and actively making late HIV proteins. These are also compared to control cells, not exposed to virus.Several observations provide new perspective on the effects of HIV-1 transcription from pre-integrated cDNA versus from integrated provirus. First, HIV-1 transcript levels do not necessarily correlate with virus production, cells harboring PIC cDNA have transcript loads comparable to cells transcribing from provirus and making p24, mCherry, and vpu proteins. Second, all HIV-1 transcripts are easily detectable in abundance from PIC cDNA transcription, as is the case with cells transcribing from provirus, although the frequency of PIC cells with detectable gag-pol, tat, env, and nef transcripts is higher than the corresponding frequencies observed for “Provirus cells”. Third, the background transcriptomes of cells harboring pre- integrated HIV-1 cDNA are not otherwise detectably altered from cells not containing any HIV- 1 transcript. Fourth, integration and production of p24, mCherry, and Vpu proteins is accompanied by a switch from transcriptomes characterized by NFkB and AP-1 promoted transcription to a transcriptome characterized by E2F family transcription products. While some of these observations may seem heretical, single cell analysis provides a more nuanced understanding of PIC cDNA transcription and the transcriptomic changes that support HIV-1 protein production from integrated provirus.Author SummarySingle cell analysis is able to distinguish between HIV-1 infected macrophage cells that are transcribing pre-integrated HIV-1 cDNA and those transcribing HIV-1 provirus. Only cells transcribing HIV-1 provirus are making p24, marker mCherry and Vpu proteins, which corresponds with a change in the host cell’s background transcriptome from one expressing viral restriction and immunological response genes to one that is expressing genes associated with cell replication and oxidative phosphorylation.

scholarly journals MBRS-59. SINGLE-CELL WHOLE-GENOME SEQUENCING DISSECTS INTRA-TUMOURAL GENOMIC HETEROGENEITY AND CLONAL EVOLUTION IN CHILDHOOD MEDULLOBLASTOMA

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii408-iii408
Author(s):  
Marina Danilenko ◽  
Masood Zaka ◽  
Claire Keeling ◽  
Stephen Crosier ◽  
Rafiqul Hussain ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Single Cell ◽  
Genome Sequencing ◽  
Copy Number ◽  
Single Cell Analysis ◽  
Mutational Analysis ◽  
Single Cells ◽  
Clonal Evolution ◽  
Whole Genome ◽  
Clinically Significant

Abstract Medulloblastomas harbor clinically-significant intra-tumoral heterogeneity for key biomarkers (e.g. MYC/MYCN, β-catenin). Recent studies have characterized transcriptional heterogeneity at the single-cell level, however the underlying genomic copy number and mutational architecture remains to be resolved. We therefore sought to establish the intra-tumoural genomic heterogeneity of medulloblastoma at single-cell resolution. Copy number patterns were dissected by whole-genome sequencing in 1024 single cells isolated from multiple distinct tumour regions within 16 snap-frozen medulloblastomas, representing the major molecular subgroups (WNT, SHH, Group3, Group4) and genotypes (i.e. MYC amplification, TP53 mutation). Common copy number driver and subclonal events were identified, providing clear evidence of copy number evolution in medulloblastoma development. Moreover, subclonal whole-arm and focal copy number alterations covering important genomic loci (e.g. on chr10 of SHH patients) were detected in single tumour cells, yet undetectable at the bulk-tumor level. Spatial copy number heterogeneity was also common, with differences between clonal and subclonal events detected in distinct regions of individual tumours. Mutational analysis of the cells allowed dissection of spatial and clonal heterogeneity patterns for key medulloblastoma mutations (e.g. CTNNB1, TP53, SMARCA4, PTCH1) within our cohort. Integrated copy number and mutational analysis is underway to establish their inter-relationships and relative contributions to clonal evolution during tumourigenesis. In summary, single-cell analysis has enabled the resolution of common mutational and copy number drivers, alongside sub-clonal events and distinct patterns of clonal and spatial evolution, in medulloblastoma development. We anticipate these findings will provide a critical foundation for future improved biomarker selection, and the development of targeted therapies.

scholarly journals In VivoTransmission of an IncA/C Plasmid in Escherichia coli Depends on Tetracycline Concentration, and Acquisition of the Plasmid Results in a Variable Cost of Fitness

2015 ◽  
Vol 81 (10) ◽  
pp. 3561-3570 ◽  
Author(s):  
Timothy J. Johnson ◽  
Randall S. Singer ◽  
Richard E. Isaacson ◽  
Jessica L. Danzeisen ◽  
Kevin Lang ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
High Dose ◽  
Broad Host Range ◽  
Antibiotic Administration ◽  
Dose Administration ◽  
Content Type ◽  
E Coli ◽  
The Impact ◽  
Selection Of

ABSTRACTIncA/C plasmids are broad-host-range plasmids enabling multidrug resistance that have emerged worldwide among bacterial pathogens of humans and animals. Although antibiotic usage is suspected to be a driving force in the emergence of such strains, few studies have examined the impact of different types of antibiotic administration on the selection of plasmid-containing multidrug resistant isolates. In this study, chlortetracycline treatment at different concentrations in pig feed was examined for its impact on selection and dissemination of an IncA/C plasmid introduced orally via a commensalEscherichia colihost. Continuous low-dose administration of chlortetracycline at 50 g per ton had no observable impact on the proportions of IncA/C plasmid-containingE. colifrom pig feces over the course of 35 days. In contrast, high-dose administration of chlortetracycline at 350 g per ton significantly increased IncA/C plasmid-containingE. coliin pig feces (P< 0.001) and increased movement of the IncA/C plasmid to other indigenousE. colihosts. There was no evidence of conjugal transfer of the IncA/C plasmid to bacterial species other thanE. coli.In vitrocompetition assays demonstrated that bacterial host background substantially impacted the cost of IncA/C plasmid carriage inE. coliandSalmonella.In vitrotransfer and selection experiments demonstrated that tetracycline at 32 μg/ml was necessary to enhance IncA/C plasmid conjugative transfer, while subinhibitory concentrations of tetracyclinein vitrostrongly selected for IncA/C plasmid-containingE. coli. Together, these experiments improve our knowledge on the impact of differing concentrations of tetracycline on the selection of IncA/C-type plasmids.

scholarly journals Studying human reproductive biology through single-cell analysis and in vitro differentiation of stem cells into germ cell-like cells

2020 ◽  
Vol 26 (5) ◽  
pp. 670-688 ◽  
Author(s):  
Lin Li ◽  
Risako Yang ◽  
Chenghong Yin ◽  
Kehkooi Kee
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Germ Cells ◽  
Regulatory Networks ◽  
Single Cell Analysis ◽  
Reproductive Development ◽  
In Vitro Differentiation ◽  
Gene Markers ◽  
Human Reproductive

Abstract BACKGROUND Understanding the molecular and cellular mechanisms of human reproductive development has been limited by the scarcity of human samples and ethical constraints. Recently, in vitro differentiation of human pluripotent stem cells into germ cells and single-cell analyses have opened new avenues to directly study human germ cells and identify unique mechanisms in human reproductive development. OBJECTIVE AND RATIONALE The goal of this review is to collate novel findings and insightful discoveries with these new methodologies, aiming at introducing researchers and clinicians to the use of these tools to study human reproductive biology and develop treatments for infertility. SEARCH METHODS PubMed was used to search articles and reviews with the following main keywords: in vitro differentiation, human stem cells, single-cell analysis, spermatogenesis, oogenesis, germ cells and other key terms related to these subjects. The search period included all publications from 2000 until now. OUTCOMES Single-cell analyses of human gonads have identified many important gene markers at different developmental stages and in subpopulations of cells. To validate the functional roles of these gene markers, researchers have used the in vitro differentiation of human pluripotent cells into germ cells and confirmed that some genetic requirements are unique in human germ cells and are not conserved in mouse models. Moreover, transcriptional regulatory networks and the interaction of germ and somatic cells in gonads were elucidated in these studies. WIDER IMPLICATIONS Single-cell analyses allow researchers to identify gene markers and potential regulatory networks using limited clinical samples. On the other hand, in vitro differentiation methods provide clinical researchers with tools to examine these newly identify gene markers and study the causative effects of mutations previously associated with infertility. Combining these two methodologies, researchers can identify gene markers and networks which are essential and unique in human reproductive development, thereby producing more accurate diagnostic tools for assessing reproductive disorders and developing treatments for infertility.

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