Evidence map›Paper›PMID 28051095›Full record

ArticleScientific reports2017

Optical High Content Nanoscopy of Epigenetic Marks Decodes Phenotypic Divergence in Stem Cells.

Joseph J Kim, Neal K Bennett, Mitchel S Devita, Sanjay Chahar, Satish Viswanath, Eunjee A Lee, Giyoung Jung, Paul P Shao, Erin P Childers, Shichong Liu and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Joseph J KimDepartment of Biomedical Engineering, Rutgers University, Piscataway, New Jersey, USA.
Neal K BennettDepartment of Biomedical Engineering, Rutgers University, Piscataway, New Jersey, USA.
Mitchel S DevitaDepartment of Cell Biology and Neuroscience, Rutgers University, Piscataway, New Jersey, USA.
Sanjay ChaharDepartment of Genetics, Rutgers University, Piscataway, New Jersey, USA.
Satish ViswanathDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Eunjee A LeeSchool of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea.
Giyoung JungSchool of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea.
Paul P ShaoDepartment of Molecular Biology, Princeton University, Princeton, New Jersey, USA.
Erin P ChildersDepartment of Polymer Science, University of Akron, Akron, Ohio, USA.
Shichong LiuEpigenetics Program, Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Anthony KulesaDepartment of Biomedical Engineering, Rutgers University, Piscataway, New Jersey, USA.
Benjamin A GarciaEpigenetics Program, Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Matthew L BeckerDepartment of Polymer Science, University of Akron, Akron, Ohio, USA.
Nathaniel S HwangSchool of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea.
Anant MadabhushiDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Michael P VerziDepartment of Genetics, Rutgers University, Piscataway, New Jersey, USA.
Prabhas V MogheDepartment of Biomedical Engineering, Rutgers University, Piscataway, New Jersey, USA.

Funding

RESBIO - the Technology Resource for Polymeric BiomaterialsP41EB001046 · NIBIB · RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK · PI KOHN, JOACHIM B. · 2003 to 2017
$17.0M
Transcriptional Mechanisms of Tumor SuppressionR01CA190558 · NCI · RUTGERS, THE STATE UNIV OF N.J. · PI MICHAEL P. VERZI · 2015 to 2026
$3.6M
Pathology Image Informatics Platform for visualization, analysis and managementU24CA199374 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI GURCAN, METIN NAFI, MADABHUSHI, ANANT · 2015 to 2019
$2.9M
Understanding the Role of Combinatorial Histone PTM PatternsR01GM110174 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI GARCIA, BENJAMIN A · 2014 to 2017
$1.3M
Decision support with MRI for targeting, evaluating laser ablation for prostate cR21CA167811 · NCI · RUTGERS, THE STATE UNIV OF N.J. · PI MADABHUSHI, ANANT · 2012 to 2013
$516k
Histologic image-based aggressiveness prediction in p16+ oropharyngeal carcinomaR21CA179327 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI MADABHUSHI, ANANT · 2014 to 2015
$389k
Computerized morphologic-molecular predictor of progression in DCISR21CA195152 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI BADVE, SUNIL S., MADABHUSHI, ANANT · 2015 to 2016
$388k
NCI NIH HHS R01 CA190558NCI NIH HHS R21 CA167811NCI NIH HHS R21 CA179327NCI NIH HHS R21 CA195152NCI NIH HHS U24 CA199374NIBIB NIH HHS P41 EB001046NIGMS NIH HHS R01 GM110174
6 · The paper itself

Abstract

While distinct stem cell phenotypes follow global changes in chromatin marks, single-cell chromatin technologies are unable to resolve or predict stem cell fates. We propose the first such use of optical high content nanoscopy of histone epigenetic marks (epi-marks) in stem cells to classify emergent cell states. By combining nanoscopy with epi-mark textural image informatics, we developed a novel approach, termed EDICTS (Epi-mark Descriptor Imaging of Cell Transitional States), to discern chromatin organizational changes, demarcate lineage gradations across a range of stem cell types and robustly track lineage restriction kinetics. We demonstrate the utility of EDICTS by predicting the lineage progression of stem cells cultured on biomaterial substrates with graded nanotopographies and mechanical stiffness, thus parsing the role of specific biophysical cues as sensitive epigenetic drivers. We also demonstrate the unique power of EDICTS to resolve cellular states based on epi-marks that cannot be detected via mass spectrometry based methods for quantifying the abundance of histone post-translational modifications. Overall, EDICTS represents a powerful new methodology to predict single cell lineage decisions by integrating high content super-resolution nanoscopy and imaging informatics of the nuclear organization of epi-marks.

Indexed as

Biological Variation, PopulationEpigenesis, GeneticCell NucleusChromatinCytological TechniquesHumansImage Processing, Computer-AssistedMesenchymal Stem CellsOptical ImagingChromatin

Identifiers

PMID28051095
PMCPMC5209743

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.