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, Xinyan Wu, Jun Zhong, Raghothama Chaerkady, Arivusudar Marimuthu, Babylakshmi Muthusamy, Nandini A. Sahasrabuddhe, Rajesh Raju, Caitlyn Bowman, Ludmila Danilova, Jevon CutlerDhanashree S. Kelkar, Charles G. Drake, T. S. Keshava Prasad, Luigi Marchionni, Peter N. Murakami, Alan F. Scott, Leming Shi, Jean Thierry-Mieg, Danielle Thierry-Mieg, Rafael Irizarry, Leslie Cope, Yasushi Ishihama, Charles Wang, Harsha Gowda, Akhilesh Pandey

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Background: Cellular 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. Results: Integrating 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. Conclusions: We 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.

Original languageEnglish (US)
Article number75
JournalBMC Systems Biology
Volume9
Issue number1
DOIs
StatePublished - Nov 6 2015
Externally publishedYes

Fingerprint

T-cells
T-Lymphocytes
RNA
Proteins
Genome
Genes
Protein
Cell Differentiation
Methylation
Biomolecules
Proteomics
High Throughput
Cell
DNA
RNA Editing
Technology
Cells
Throughput
Differentiation Antigens
Data storage equipment

Keywords

  • Epigenomics
  • Innate immunity
  • Integrative -omics
  • Phosphoproteomics
  • Proteomics
  • Transcriptomics
  • Whole genome sequencing

ASJC Scopus subject areas

  • Structural Biology
  • Modeling and Simulation
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

Cite this

Mitchell, C. J., Getnet, D., Kim, M. S., Manda, S. S., Kumar, P., Huang, T. C., ... Pandey, A. (2015). A multi-omic analysis of human naïve CD4+ T cells. BMC Systems Biology, 9(1), [75]. https://doi.org/10.1186/s12918-015-0225-4

A multi-omic analysis of human naïve CD4+ T cells. / Mitchell, Christopher J.; Getnet, Derese; Kim, Min Sik; Manda, Srikanth S.; Kumar, Praveen; Huang, Tai Chung; Pinto, Sneha M.; Nirujogi, Raja Sekhar; Iwasaki, Mio; Shaw, Patrick G.; Wu, Xinyan; Zhong, Jun; Chaerkady, Raghothama; Marimuthu, Arivusudar; Muthusamy, Babylakshmi; Sahasrabuddhe, Nandini A.; Raju, Rajesh; Bowman, Caitlyn; Danilova, Ludmila; Cutler, Jevon; Kelkar, Dhanashree S.; Drake, Charles G.; Keshava Prasad, T. S.; Marchionni, Luigi; Murakami, Peter N.; Scott, Alan F.; Shi, Leming; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Irizarry, Rafael; Cope, Leslie; Ishihama, Yasushi; Wang, Charles; Gowda, Harsha; Pandey, Akhilesh.

In: BMC Systems Biology, Vol. 9, No. 1, 75, 06.11.2015.

Research output: Contribution to journalArticle

Mitchell, CJ, Getnet, D, Kim, MS, Manda, SS, Kumar, P, Huang, TC, Pinto, SM, Nirujogi, RS, Iwasaki, M, Shaw, PG, Wu, X, Zhong, J, Chaerkady, R, Marimuthu, A, Muthusamy, B, Sahasrabuddhe, NA, Raju, R, Bowman, C, Danilova, L, Cutler, J, Kelkar, DS, Drake, CG, Keshava Prasad, TS, Marchionni, L, Murakami, PN, Scott, AF, Shi, L, Thierry-Mieg, J, Thierry-Mieg, D, Irizarry, R, Cope, L, Ishihama, Y, Wang, C, Gowda, H & Pandey, A 2015, 'A multi-omic analysis of human naïve CD4+ T cells', BMC Systems Biology, vol. 9, no. 1, 75. https://doi.org/10.1186/s12918-015-0225-4
Mitchell CJ, Getnet D, Kim MS, Manda SS, Kumar P, Huang TC et al. A multi-omic analysis of human naïve CD4+ T cells. BMC Systems Biology. 2015 Nov 6;9(1). 75. https://doi.org/10.1186/s12918-015-0225-4
Mitchell, Christopher J. ; Getnet, Derese ; Kim, Min Sik ; Manda, Srikanth S. ; Kumar, Praveen ; Huang, Tai Chung ; Pinto, Sneha M. ; Nirujogi, Raja Sekhar ; Iwasaki, Mio ; Shaw, Patrick G. ; Wu, Xinyan ; Zhong, Jun ; Chaerkady, Raghothama ; Marimuthu, Arivusudar ; Muthusamy, Babylakshmi ; Sahasrabuddhe, Nandini A. ; Raju, Rajesh ; Bowman, Caitlyn ; Danilova, Ludmila ; Cutler, Jevon ; Kelkar, Dhanashree S. ; Drake, Charles G. ; Keshava Prasad, T. S. ; Marchionni, Luigi ; Murakami, Peter N. ; Scott, Alan F. ; Shi, Leming ; Thierry-Mieg, Jean ; Thierry-Mieg, Danielle ; Irizarry, Rafael ; Cope, Leslie ; Ishihama, Yasushi ; Wang, Charles ; Gowda, Harsha ; Pandey, Akhilesh. / A multi-omic analysis of human naïve CD4+ T cells. In: BMC Systems Biology. 2015 ; Vol. 9, No. 1.
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abstract = "Background: Cellular 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 na{\"i}ve CD4+ T cells isolated from a single individual. Results: Integrating 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 na{\"i}ve CD4+ T cells. In addition, we carried out a multi-omic comparative analysis of na{\"i}ve 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. Conclusions: We utilized multiple high-throughput technologies to derive a comprehensive profile of two primary human cell types, na{\"i}ve 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.",
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author = "Mitchell, {Christopher J.} and Derese Getnet and Kim, {Min Sik} and Manda, {Srikanth S.} and Praveen Kumar and Huang, {Tai Chung} and Pinto, {Sneha M.} and Nirujogi, {Raja Sekhar} and Mio Iwasaki and Shaw, {Patrick G.} and Xinyan Wu and Jun Zhong and Raghothama Chaerkady and Arivusudar Marimuthu and Babylakshmi Muthusamy and Sahasrabuddhe, {Nandini A.} and Rajesh Raju and Caitlyn Bowman and Ludmila Danilova and Jevon Cutler and Kelkar, {Dhanashree S.} and Drake, {Charles G.} and {Keshava Prasad}, {T. S.} and Luigi Marchionni and Murakami, {Peter N.} and Scott, {Alan F.} and Leming Shi and Jean Thierry-Mieg and Danielle Thierry-Mieg and Rafael Irizarry and Leslie Cope and Yasushi Ishihama and Charles Wang and Harsha Gowda and Akhilesh Pandey",
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T1 - A multi-omic analysis of human naïve CD4+ T cells

AU - Mitchell, Christopher J.

AU - Getnet, Derese

AU - Kim, Min Sik

AU - Manda, Srikanth S.

AU - Kumar, Praveen

AU - Huang, Tai Chung

AU - Pinto, Sneha M.

AU - Nirujogi, Raja Sekhar

AU - Iwasaki, Mio

AU - Shaw, Patrick G.

AU - Wu, Xinyan

AU - Zhong, Jun

AU - Chaerkady, Raghothama

AU - Marimuthu, Arivusudar

AU - Muthusamy, Babylakshmi

AU - Sahasrabuddhe, Nandini A.

AU - Raju, Rajesh

AU - Bowman, Caitlyn

AU - Danilova, Ludmila

AU - Cutler, Jevon

AU - Kelkar, Dhanashree S.

AU - Drake, Charles G.

AU - Keshava Prasad, T. S.

AU - Marchionni, Luigi

AU - Murakami, Peter N.

AU - Scott, Alan F.

AU - Shi, Leming

AU - Thierry-Mieg, Jean

AU - Thierry-Mieg, Danielle

AU - Irizarry, Rafael

AU - Cope, Leslie

AU - Ishihama, Yasushi

AU - Wang, Charles

AU - Gowda, Harsha

AU - Pandey, Akhilesh

PY - 2015/11/6

Y1 - 2015/11/6

N2 - Background: Cellular 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. Results: Integrating 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. Conclusions: We 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.

AB - Background: Cellular 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. Results: Integrating 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. Conclusions: We 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.

KW - Epigenomics

KW - Innate immunity

KW - Integrative -omics

KW - Phosphoproteomics

KW - Proteomics

KW - Transcriptomics

KW - Whole genome sequencing

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