Systems Approaches towards Molecular Profiling of Human Immunity

Trends in Immunology

Volumn 37, Issue 1, 2016, Pages 53-67

  Burel, Julie G ^a,b   Apte, Simon H ^a   Doolan, Denise L ^a,b  

^a QIMR BERGHOFER MEDICAL RESEARCH INSTITUTE   (Australia)

^b UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIBODY; ANTIGEN; UNTRANSLATED RNA;

BIOINFORMATICS; EPIGENETICS; FLOW CYTOMETRY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENETIC ANALYSIS; GENETIC POLYMORPHISM; GENOMICS; HOST PATHOGEN INTERACTION; HUMAN; IMMUNE RESPONSE; IMMUNITY; IMMUNOLOGY; INFECTION; METABOLOMICS; PROTEIN EXPRESSION; PROTEOMICS; QUANTITATIVE TRAIT LOCUS; REVIEW; SINGLE CELL ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM; T LYMPHOCYTE; TRANSCRIPTOMICS; ANIMAL; BIOLOGY; GENETICS; MOLECULAR PATHOLOGY; PROCEDURES; SYSTEMS BIOLOGY; TRENDS;

ALLERGY AND IMMUNOLOGY; ANIMALS; COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; HOST-PATHOGEN INTERACTIONS; HUMANS; IMMUNITY; PATHOLOGY, MOLECULAR; SINGLE-CELL ANALYSIS; SYSTEMS BIOLOGY;

EID: 84952864342     PISSN: 14714906     EISSN: 14714981     Source Type: Journal    
DOI: 10.1016/j.it.2015.11.006     Document Type: Review

References (104)

1. Davis M.M. A prescription for human immunology. Immunity 2008, 29:835-838.
2. Hoffman S.L., et al. Protection of humans against malaria by immunization with radiation-attenuated Plasmodium falciparum sporozoites. J. Infect. Dis. 2002, 185:1155-1164.
3. Roestenberg M., et al. Long-term protection against malaria after experimental sporozoite inoculation: an open-label follow-up study. Lancet 2011, 377:1770-1776.
4. Engwerda C.R., et al. Experimentally induced blood stage malaria infection as a tool for clinical research. Trends Parasitol. 2012, 28:515-521.
5. Nakaya H.I., et al. Systems biology of vaccination for seasonal influenza in humans. Nat. Immunol. 2011, 12:786-795.
6. Querec T.D., et al. Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans. Nat. Immunol. 2009, 10:116-125.
7. Kennedy R.B., et al. Transcriptomic profiles of high and low antibody responders to smallpox vaccine. Genes Immun. 2013, 14:277-285.
8. Obermoser G., et al. Systems scale interactive exploration reveals quantitative and qualitative differences in response to influenza and pneumococcal vaccines. Immunity 2013, 38:831-844.
9. Hu H., et al. Distinct gene-expression profiles associated with the susceptibility of pathogen-specific CD4 T cells to HIV-1 infection. Blood 2013, 121:1136-1144.
10. Ockenhouse C.F., et al. Common and divergent immune response signaling pathways discovered in peripheral blood mononuclear cell gene expression patterns in presymptomatic and clinically apparent malaria. Infect. Immun. 2006, 74:5561-5573.
11. Berry M.P., et al. An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis. Nature 2010, 466:973-977.
12. Dominguez M.H., et al. Highly multiplexed quantitation of gene expression on single cells. J. Immunol. Methods 2013, 391:133-145.
13. Feinerman O., et al. Single-cell quantification of IL-2 response by effector and regulatory T cells reveals critical plasticity in immune response. Mol. Syst. Biol. 2010, 6:437.
14. Flatz L., et al. Single-cell gene-expression profiling reveals qualitatively distinct CD8 T cells elicited by different gene-based vaccines. Proc. Natl. Acad. Sci. U.S.A. 2011, 108:5724-5729.
15. + T lymphocyte fates during adaptive immunity revealed by single-cell gene-expression analyses. Nat. Immunol. 2014, 15:365-372.
16. Shapiro E., et al. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat. Rev. Genet. 2013, 14:618-630.
17. Shalek A.K., et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 2013, 498:236-240.
18. Klein A.M., et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 2015, 161:1187-1201.
19. Macosko E.Z., et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 2015, 161:1202-1214.
20. Carninci P., et al. The transcriptional landscape of the mammalian genome. Science 2005, 309:1559-1563.
21. Kellis M., et al. Defining functional DNA elements in the human genome. Proc. Natl. Acad. Sci. U.S.A. 2014, 111:6131-6138.
22. Fu Y., et al. Circulating microRNAs in patients with active pulmonary tuberculosis. J. Clin. Microbiol. 2011, 49:4246-4251.
23. Ji F., et al. Circulating microRNAs in hepatitis B virus-infected patients. J. Viral Hepat. 2011, 18:e242-e251.
24. Reynoso R., et al. MicroRNAs differentially present in the plasma of HIV elite controllers reduce HIV infection in vitro. Sci. Rep. 2014, 4:5915.
25. + T lymphocyte miRNA expression after exposure to HIV-1. Blood 2012, 119:6259-6267.
26. Fitzgerald K.A., Caffrey D.R. Long noncoding RNAs in innate and adaptive immunity. Curr. Opin. Immunol. 2014, 26:140-146.
27. Heward J.A., Lindsay M.A. Long non-coding RNAs in the regulation of the immune response. Trends Immunol. 2014, 35:408-419.
28. Kleinnijenhuis J., et al. Bacille Calmette-Guerin induces NOD2-dependent nonspecific protection from reinfection via epigenetic reprogramming of monocytes. Proc. Natl. Acad. Sci. U.S.A. 2012, 109:17537-17542.
29. Denton A.E., et al. Differentiation-dependent functional and epigenetic landscapes for cytokine genes in virus-specific CD8+ T cells. Proc. Natl. Acad. Sci. U.S.A. 2011, 108:15306-15311.
30. Kanno Y., et al. Transcriptional and epigenetic control of T helper cell specification: molecular mechanisms underlying commitment and plasticity. Annu. Rev. Immunol. 2012, 30:707-731.
31. Poland G.A., et al. Heterogeneity in vaccine immune response: the role of immunogenetics and the emerging field of vaccinomics. Clin. Pharmacol. Ther. 2007, 82:653-664.
32. Haralambieva I.H., et al. The genetic basis for interindividual immune response variation to measles vaccine: new understanding and new vaccine approaches. Expert Rev. Vaccines 2013, 12:57-70.
33. Azad A.K., et al. Innate immune gene polymorphisms in tuberculosis. Infect. Immun. 2012, 80:3343-3359.
34. Gibson G., et al. Expression quantitative trait locus analysis for translational medicine. Genome Med. 2015, 7:60.
35. Darrah P.A., et al. Multifunctional TH1 cells define a correlate of vaccine-mediated protection against Leishmania major. Nat. Med. 2007, 13:843-850.
36. Lindenstrom T., et al. Tuberculosis subunit vaccination provides long-term protective immunity characterized by multifunctional CD4 memory T cells. J. Immunol. 2009, 182:8047-8055.
37. + T cells. Blood 2006, 107:4781-4789.
38. Prezzemolo T., et al. Functional signatures of human CD4 and CD8 T cell responses to Mycobacterium tuberculosis. Front. Immunol. 2014, 5:180.
39. Chattopadhyay P.K., et al. A chromatic explosion: the development and future of multiparameter flow cytometry. Immunology 2008, 125:441-449.
40. + T cell phenotypes. Immunity 2012, 36:142-152.
41. Elshal M.F., McCoy J.P. Multiplex bead array assays: performance evaluation and comparison of sensitivity to ELISA. Methods 2006, 38:317-323.
42. Walther M., et al. Innate immune responses to human malaria: heterogeneous cytokine responses to blood-stage Plasmodium falciparum correlate with parasitological and clinical outcomes. J. Immunol. 2006, 177:5736-5745.
43. Reif D.M., et al. Integrated analysis of genetic and proteomic data identifies biomarkers associated with adverse events following smallpox vaccination. Genes Immun. 2009, 10:112-119.
44. Wu S., et al. Development and application of 'phosphoflow' as a tool for immunomonitoring. Expert Rev. Vaccines 2010, 9:631-643.
45. Perez O.D., Nolan G.P. Phospho-proteomic immune analysis by flow cytometry: from mechanism to translational medicine at the single-cell level. Immunol. Rev. 2006, 210:208-228.
46. Lee A.W., et al. Single-cell, phosphoepitope-specific analysis demonstrates cell type- and pathway-specific dysregulation of Jak/STAT and MAPK signaling associated with in vivo human immunodeficiency virus type 1 infection. J. Virol. 2008, 82:3702-3712.
47. Bendall S.C., et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 2011, 332:687-696.
48. Newell E.W., Davis M.M. Beyond model antigens: high-dimensional methods for the analysis of antigen-specific T cells. Nat. Biotechnol. 2014, 32:149-157.
49. Qi Q., et al. Diversity and clonal selection in the human T-cell repertoire. Proc. Natl. Acad. Sci. U.S.A. 2014, 111:13139-13144.
50. + alphabeta T cells and gammadelta T cells in celiac disease. Proc. Natl. Acad. Sci. U.S.A. 2013, 110:13073-13078.
51. Newell E.W., et al. Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization. Nat. Biotechnol. 2013, 31:623-629.
52. Davies D.H., et al. Profiling the humoral immune response to infection by using proteome microarrays: high-throughput vaccine and diagnostic antigen discovery. Proc. Natl. Acad. Sci. U.S.A. 2005, 102:547-552.
53. Davies D.H., et al. Large screen approaches to identify novel malaria vaccine candidates. Vaccine 2015, Published online October 1, 2015. 10.1016/j.vaccine.2015.09.059.
54. Legutki J.B., et al. A general method for characterization of humoral immunity induced by a vaccine or infection. Vaccine 2010, 28:4529-4537.
55. Georgiou G., et al. The promise and challenge of high-throughput sequencing of the antibody repertoire. Nat. Biotechnol. 2014, 32:158-168.
56. Wang C., et al. Effects of aging, cytomegalovirus infection, and EBV infection on human B cell repertoires. J. Immunol. 2014, 192:603-611.
57. Truck J., et al. Identification of antigen-specific B cell receptor sequences using public repertoire analysis. J. Immunol. 2015, 194:252-261.
58. Shapira S.D., et al. A physical and regulatory map of host-influenza interactions reveals pathways in H1N1 infection. Cell 2009, 139:1255-1267.
59. de Chassey B., et al. Hepatitis C virus infection protein network. Mol. Syst. Biol. 2008, 4:230.
60. Uetz P., et al. Herpesviral protein networks and their interaction with the human proteome. Science 2006, 311:239-242.
61. Calderwood M.A., et al. Epstein-Barr virus and virus human protein interaction maps. Proc. Natl. Acad. Sci. U.S.A. 2007, 104:7606-7611.
62. Tribolet L., et al. Probing of a human proteome microarray with a recombinant pathogen protein reveals a novel mechanism by which hookworms suppress b-cell receptor signaling. J. Infect. Dis. 2014, 211:416-425.
63. Cui L., et al. Serum metabolome and lipidome changes in adult patients with primary dengue infection. PLoS Negl. Trop. Dis. 2013, 7:e2373.
64. Cribbs S.K., et al. Metabolomics of bronchoalveolar lavage differentiate healthy HIV-1-infected subjects from controls. AIDS Res. Hum. Retroviruses 2014, 30:579-585.
65. Kruh-Garcia N.A., et al. Detection of Mycobacterium tuberculosis peptides in the exosomes of patients with active and latent M. tuberculosis infection using MRM-MS. PLoS ONE 2014, 9:e103811.
66. Mahapatra S., et al. A metabolic biosignature of early response to anti-tuberculosis treatment. BMC Infect. Dis. 2014, 14:53.
67. Wikoff W.R., et al. Response and recovery in the plasma metabolome tracks the acute LCMV-induced immune response. J. Proteome Res. 2009, 8:3578-3587.
68. Munger J., et al. Systems-level metabolic flux profiling identifies fatty acid synthesis as a target for antiviral therapy. Nat. Biotechnol. 2008, 26:1179-1186.
69. Olszewski K.L., et al. Host-parasite interactions revealed by Plasmodium falciparum metabolomics. Cell Host Microbe 2009, 5:191-199.
70. Mooney M., et al. A systems framework for vaccine design. Curr. Opin. Immunol. 2013, 25:551-555.
71. Brehm M.A., et al. Overcoming current limitations in humanized mouse research. J. Infect. Dis. 2013, 208(Suppl. 2):S125-S130.
72. Gonzalez L., et al. Humanized mice: novel model for studying mechanisms of human immune-based therapies. Immunol. Res. 2013, 57:326-334.
73. Shen-Orr S.S., et al. Cell type-specific gene expression differences in complex tissues. Nat. Methods 2010, 7:287-289.
74. Chaussabel D., Baldwin N. Democratizing systems immunology with modular transcriptional repertoire analyses. Nat. Rev. Immunol. 2014, 14:271-280.
75. Benoist C., et al. A plaidoyer for 'systems immunology'. Immunol. Rev. 2006, 210:229-234.
76. Maecker H.T., et al. Standardizing immunophenotyping for the Human Immunology Project. Nat. Rev. Immunol. 2012, 12:191-200.
77. Shannon P., et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13:2498-2504.
78. Bindea G., et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 2009, 25:1091-1093.
79. Bindea G., et al. CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data. Bioinformatics 2013, 29:661-663.
80. Reddy B.P., et al. A bioinformatic survey of RNA-binding proteins in Plasmodium. BMC Genomics 2015, 16:890.
81. Breuer K., et al. InnateDB: systems biology of innate immunity and beyond: recent updates and continuing curation. Nucleic Acids Res. 2013, 41:D1228-D1233.
82. Gordon S.B., et al. The alveolar microenvironment of patients infected with human immunodeficiency virus does not modify alveolar macrophage interactions with Streptococcus pneumoniae. Clin. Vaccine Immunol. 2013, 20:882-891.
83. Goh K.I., et al. The human disease network. Proc. Natl. Acad. Sci. U.S.A. 2007, 104:8685-8690.
84. Qiu P., et al. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat. Biotechnol. 2011, 29:886-891.
85. Amir el A.D., et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat. Biotechnol. 2013, 31:545-552.
86. Finak G., et al. Mixture models for single-cell assays with applications to vaccine studies. Biostatistics 2014, 15:87-101.
87. Lin L., et al. COMPASS identifies T-cell subsets correlated with clinical outcomes. Nat. Biotechnol. 2015, 33:601-616.
88. Nakaya H.I., et al. Systems vaccinology: learning to compute the behavior of vaccine induced immunity. Wiley Interdiscip. Rev. Syst. Biol. Med. 2012, 4:193-205.
89. Vahey M.T., et al. Expression of genes associated with immunoproteasome processing of major histocompatibility complex peptides is indicative of protection with adjuvanted RTS,S malaria vaccine. J. Infect. Dis. 2010, 201:580-589.
90. Barabasi A.L., et al. Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 2011, 12:56-68.
91. Amit I., et al. Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses. Science 2009, 326:257-263.
92. Chevrier N., et al. Systematic discovery of TLR signaling components delineates viral-sensing circuits. Cell 2011, 147:853-867.
93. Meyer S.U., et al. Posttranscriptional regulatory networks: from expression profiling to integrative analysis of mRNA and microRNA data. Methods Mol. Biol. 2014, 1160:165-188.
94. Siebert J.C., et al. Integrating and mining diverse data in human immunological studies. Bioanalysis 2014, 6:209-223.
95. Aghaeepour N., et al. Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays. Bioinformatics 2012, 28:1009-1016.
96. Tsang J.S., et al. Global analyses of human immune variation reveal baseline predictors of postvaccination responses. Cell 2014, 157:499-513.
97. Germain R.N., et al. Systems biology in immunology: a computational modeling perspective. Annu. Rev. Immunol. 2011, 29:527-585.
98. Poland G.A., et al. Understanding the human immune system in the 21st century: the Human Immunology Project Consortium. Vaccine 2013, 31:2911-2912.
99. Aderem A., et al. A systems biology approach to infectious disease research: innovating the pathogen-host research paradigm. MBio 2011, 2:e00325-10.
100. Konig R., et al. Human host factors required for influenza virus replication. Nature 2010, 463:813-817.
101. Galagan J.E., et al. The Mycobacterium tuberculosis regulatory network and hypoxia. Nature 2013, 499:178-183.
102. Bhattacharya S., et al. ImmPort: disseminating data to the public for the future of immunology. Immunol. Res. 2014, 58:234-239.
103. Shay T., Kang J. Immunological Genome Project and systems immunology. Trends Immunol. 2013, 34:602-609.
104. Kim C.C., Lanier L.L. Beyond the transcriptome: completion of act one of the Immunological Genome Project. Curr. Opin. Immunol. 2013, 25:593-597.