Evidence map›Paper›PMID 26542228›Full record

ArticleBMC systems biology2015

A multi-omic analysis of human naïve CD4+ T cells.

Christopher J Mitchell, Derese Getnet, Min-Sik Kim, Srikanth S Manda, Praveen Kumar, Tai-Chung Huang, Sneha M Pinto, Raja Sekhar Nirujogi, Mio Iwasaki, Patrick G Shaw and 25 more

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
2.7field-weighted citation impact, top 9% of its field
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

25 citing papers in PubMed, 43 citations in OpenAlex.

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  5. Characterization of proteogenomic signatures of differentiation of CD4+ T cell subsets.DNA research : an international journal for rapid publication of reports on genes and genomes · 2023
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  9. Modeling the Th17 and Tregs Paradigm: Implications for Cancer Immunotherapy.Frontiers in cell and developmental biology · 2021
    Review
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  15. Article
  16. Article
  17. Multi-OMICS analyses unveilAnnals of the rheumatic diseases · 2018
    Article
  18. Review
  19. Review
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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

35 authors at 10 institutions in 3 countries.

Christopher J MitchellMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. cmitch48@jhmi.edu.
Derese GetnetMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. dgetnet1@jhmi.edu.
Min-Sik KimMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. mskim@jhmi.edu.
Srikanth S MandaInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. srikanth@ibioinformatics.org.
Praveen KumarInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. praveen@ibioinformatics.org.
Tai-Chung HuangMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. huang@jhmi.edu.
Sneha M PintoInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. pinto@jhmi.edu.
Raja Sekhar NirujogiInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. raja@ibioinformatics.org.
Mio IwasakiDepartment of Molecular & Cellular BioAnalysis, Kyoto University, Kyoto, Japan. omio13@gmail.com.
Patrick G ShawMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. pshaw@jhsph.edu.
Xinyan WuMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. xinyan@jhmi.edu.
Jun ZhongMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jzhong@jhmi.edu.
Raghothama ChaerkadyMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. raghothama@jhmi.edu.
Arivusudar MarimuthuInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. arivusudar@ibioinformatics.org.
Babylakshmi MuthusamyInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. babylakshmi@ibioinformatics.org.
Nandini A SahasrabuddheInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. nandini@ibioinformatics.org.
Rajesh RajuInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. rajesh@ibioinformatics.org.
Caitlyn BowmanMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. cbowma14@jhmi.edu.
Ludmila DanilovaSidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. ludmila.danilova@gmail.com.
Jevon CutlerMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jevon@jhmi.edu.
Dhanashree S KelkarInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. dhanashree@ibioinformatics.org.
Charles G DrakeSidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. cdrake@jhmi.edu.
T S Keshava PrasadInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. keshav@ibioinformatics.org.
Luigi MarchionniSidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. marchion@gmail.com.
Peter N MurakamiDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. pmurakam@jhsph.edu.
Alan F ScottMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. afscott@jhmi.edu.
Leming ShiNational Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA. leming.shi@fda.hhs.gov.
Jean Thierry-MiegNational Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA. mieg@ncbi.nlm.nih.gov.
Danielle Thierry-MiegNational Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA. mieg@ncbi.nlm.nih.gov.
Rafael IrizarryDepartment of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA, USA. rafa@jhu.edu.
Leslie CopeSidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Lcope1@jhmi.edu.
Yasushi IshihamaDepartment of Molecular & Cellular BioAnalysis, Kyoto University, Kyoto, Japan. yishiham@pharm.kyoto-u.ac.jp.
Charles WangCenter for Genomics and Division of Microbiology & Molecular Genetics, Loma Linda University, Loma Linda, CA, USA. chwang@llu.edu.
Harsha GowdaInstitute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. harsha@bioinformatics.org.
Akhilesh PandeyMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. pandey@jhmi.edu.
Institute of Bioinformatics · INJohns Hopkins University · USJohns Hopkins Medicine · USKyoto University · JPSidney Kimmel Comprehensive Cancer Center · USDana-Farber Cancer Institute · USLoma Linda University · USNational Center for Biotechnology Information · USNational Center for Toxicological Research · USNational Institutes of Health · US

Funding

Proteome Characterization Center: A Genoproteomics Pipeline for Cance ResearchU24CA160036 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI, ZHANG, HUI · 2011 to 2016
$10.7M
Predoctoral Training Program in Human GeneticsT32GM007814 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI VALLE, DAVID · 1985 to 2021
$10.6M
Networks, Pathways and Dynamics of Lysine ModificationU54GM103520 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BADER, JOEL S. · 2012 to 2013
$7.0M
NCI NIH HHS U24 CA160036NCI NIH HHS U24CA160036NHLBI NIH HHS HHSN268201000032CNIGMS NIH HHS T32 GM007814NIGMS NIH HHS U54 GM103520NIGMS NIH HHS U54GM103520Wellcome Trust
6 · The paper itself

Abstract

backgroundCellular function and diversity are orchestrated by complex interactions of fundamental biomolecules including DNA, RNA and proteins. Technological advances in genomics, epigenomics, transcriptomics and proteomics have enabled massively parallel and unbiased measurements. Such high-throughput technologies have been extensively used to carry out broad, unbiased studies, particularly in the context of human diseases. Nevertheless, a unified analysis of the genome, epigenome, transcriptome and proteome of a single human cell type to obtain a coherent view of the complex interplay between various biomolecules has not yet been undertaken. Here, we report the first multi-omic analysis of human primary naïve CD4+ T cells isolated from a single individual.

resultsIntegrating multi-omics datasets allowed us to investigate genome-wide methylation and its effect on mRNA/protein expression patterns, extent of RNA editing under normal physiological conditions and allele specific expression in naïve CD4+ T cells. In addition, we carried out a multi-omic comparative analysis of naïve with primary resting memory CD4+ T cells to identify molecular changes underlying T cell differentiation. This analysis provided mechanistic insights into how several molecules involved in T cell receptor signaling are regulated at the DNA, RNA and protein levels. Phosphoproteomics revealed downstream signaling events that regulate these two cellular states. Availability of multi-omics data from an identical genetic background also allowed us to employ novel proteogenomics approaches to identify individual-specific variants and putative novel protein coding regions in the human genome.

conclusionsWe utilized multiple high-throughput technologies to derive a comprehensive profile of two primary human cell types, naïve CD4+ T cells and memory CD4+ T cells, from a single donor. Through vertical as well as horizontal integration of whole genome sequencing, methylation arrays, RNA-Seq, miRNA-Seq, proteomics, and phosphoproteomics, we derived an integrated and comparative map of these two closely related immune cells and identified potential molecular effectors of immune cell differentiation following antigen encounter.

Indexed as

Models, BiologicalCD4-Positive T-LymphocytesDNA MethylationEpigenomicsGene Expression ProfilingGenetic VariationGenome, HumanGenomicsHigh-Throughput Nucleotide SequencingHumansImmunity, InnatePhosphorylationProteomicsRNA EditingRNA, MessengerSignal TransductionRNA, Messenger

Identifiers

PMID26542228
PMCPMC4636073
OpenAlexW2163533036

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.