DOI: 10.1126/science.294.5543.870. The Plasticity of Dendritic Cell Responses to Pathogens and Their Components

The Plasticity of Dendritic Cell Responses to Pathogens and Their Components

10.1126/science.294.5543.870

Crossref journal-article

American Association for the Advancement of Science (AAAS)

Science (221)

Abstract

Dendritic cells are involved in the initiation of both innate and adaptive immunity. To systematically explore how dendritic cells modulate the immune system in response to different pathogens, we used oligonucleotide microarrays to measure gene expression profiles of dendritic cells in response to Escherichia coli , Candida albicans , and influenza virus as well as to their molecular components. Both a shared core response and pathogen-specific programs of gene expression were observed upon exposure to each of these pathogens. These results reveal that dendritic cells sense diverse pathogens and elicit tailored pathogen-specific immune responses.

Bibliography

Huang, Q., Liu, D., Majewski, P., Schulte, L. C., Korn, J. M., Young, R. A., Lander, E. S., & Hacohen, N. (2001). The Plasticity of Dendritic Cell Responses to Pathogens and Their Components. Science, 294(5543), 870â875.

Authors 8

Qian Huang (first)
Dongyu Liu (additional)
Paul Majewski (additional)
Leah C. Schulte (additional)
Joshua M. Korn (additional)
Richard A. Young (additional)
Eric S. Lander (additional)
Nir Hacohen (additional)

References 40 Referenced 605

Medzhitov R., Janeway C., Immunol. Rev. 173, 89 (2000). (10.1034/j.1600-065X.2000.917309.x) / Immunol. Rev. by Medzhitov R. (2000)
Aderem A., Ulevitch R. J., Nature 406, 782 (2000). (10.1038/35021228) / Nature by Aderem A. (2000)
10.1016/S1074-7613(01)00136-4
10.1038/32588
10.1038/4447
Elutriated human monocytes (Advanced Biotechnology Inc.) were differentiated into DCs for 7 days in standard conditions with granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-4 (12 30).
Pathogens or their components were added to DC cultures (10 7 cells per plate per time point) at day 7 at the following amounts: E. coli SD54 (ATCC) [multiplicity of infection (MOI) 5:1] Influenza A/PR/8/34 (750 HAU/ml) Candida albicans HLC54 (5:1 MOI) LPS from E. coli 055:B5 (1 μg/ml Sigma L-2880) polyinosine-polycytidine (25 μg/ml Pharmacia; endotoxin levels were <0.2 EU/ml) and mannan from > S. cerevisiae (1 mg/ml Sigma M-7504). See (12).
Total RNA at each time point was isolated labeled and prepared for hybridization to HuGeneFL oligonucleotide arrays (Affymetrix) using standard methods (12 37).
Gene expression measurements were stored analyzed and visualized using a set of database and analysis tools developed in the lab. Messenger RNA expression kinetics and induction levels were validated with enzyme-linked immunosorbent assay (ELISA) measurement of tumor necrosis factor (TNF) α IL-12/p40 IL-10 and MCP-1 protein levels (12).
A scoring system was developed to measure significant change in stimulated expression levels relative to control time course. We collected a time series of mRNA fluorescence levels R = { R 1 R 2 R 3 … R n } in DCs exposed to each pathogen or compound and a control series of mRNA levels C = { C 1 C 2 C 3 … C n } in untreated DCs from the same donor. R i and C i are steady-state mRNA hybridization measurements (“average difference” in Affymetrix terminology) at the i th time point; n is the total number of time points. We devised a score S i = ( R i − μ C )/σ C to measure deviation of the stimulated expression level at one time point R i from the mean μ C of all the time points in the control time course. By using σ C the standard deviation of the control time course the score penalizes genes with high noise in the media control thus allowing us to extract the most robust data. Up-regulated and down-regulated genes were selected according to criteria described in (12).
Stimulus-specific genes (Figs. 1 and 3 stippled circles) were selected if the ratio of relative expression levels between stimuli was larger than 2.5 or if the data passed a stringent stimulus-specific filter based on the score (12).
Supplementary information is available on Science Online (www.sciencemag.org/cgi/content/full/294/5543/870/DC1) and our lab's Web site ().
A self-organizing map algorithm (38) was used to cluster genes on the basis of similarity of their temporal expression profiles and allowed us to classify genes into six groups: genes that peak at early middle or late phases of the time course and for each of these genes that are expressed transiently or in a sustained fashion (Fig. 2A). We also assigned each of the regulated genes to functional categories according to the public databases and the Proteome annotated database (Human PSD kindly provided through a collaboration with Proteome Inc.).
F. Sallusto et al. Eur. J. Immunol. 29 1617 (1999). (10.1002/(SICI)1521-4141(199905)29:05<1617::AID-IMMU1617>3.0.CO;2-3)
10.1056/NEJM200010053431407
L. A. O'Reilly
Strasser A., Inflamm. Res. 48, 5 (1999). / Inflamm. Res. by Strasser A. (1999)
10.1016/S0955-0674(99)00022-8
10.1242/jeb.203.8.1253
10.1146/annurev.immunol.16.1.225
Braun M. C., Lahey E., Kelsall B. L., J. Immunol. 164, 3009 (2000). (10.4049/jimmunol.164.6.3009) / J. Immunol. by Braun M. C. (2000)
P. Tomasec et al. Science 287 1031 (2000). (10.1126/science.287.5455.1031)
Milstien S., Jaffe H., Kowlessur D., Bonner T. I., J. Biol. Chem. 271, 19743 (1996). (10.1074/jbc.271.33.19743) / J. Biol. Chem. by Milstien S. (1996)
P. Hwu et al. J. Immunol. 164 3596 (2000). (10.4049/jimmunol.164.7.3596)
S. I. Hashimoto et al. Blood 96 2206 (2000). (10.1182/blood.V96.6.2206)
Dietz A. B., Bulur P. A., Knutson G. J., Matasic R., Vuk-Pavlovic S., Biochem. Biophys. Res. Commun. 275, 731 (2000). (10.1006/bbrc.2000.3372) / Biochem. Biophys. Res. Commun. by Dietz A. B. (2000)
Ashman R. B., Papadimitriou J. M., Microbiol. Rev. 59, 646 (1995). (10.1128/mr.59.4.646-672.1995) / Microbiol. Rev. by Ashman R. B. (1995)
Ludwig S., Pleschka S., Wolff T., Viral Immunol. 12, 175 (1999). (10.1089/vim.1999.12.175) / Viral Immunol. by Ludwig S. (1999)
10.1016/S0952-7915(99)80066-1
Q. Huang D. Liu N. Hacohen unpublished data.
M. Cella et al. J. Exp. Med. 189 821 (1999). (10.1084/jem.189.5.821)
N. Bhardwaj et al. J. Clin. Invest. 94 797 (1994). (10.1172/JCI117399)
M. Rescigno et al. Proc. Natl. Acad. Sci. U.S.A. 95 5229 (1998). (10.1073/pnas.95.9.5229)
H. Hemmi et al. Nature 408 740 (2000). (10.1038/35047123)
M. C. Rissoan et al. Science 283 1183 (1999). (10.1126/science.283.5405.1183)
J. Banchereau et al. Annu. Rev. Immunol. 18 767 (2000). (10.1146/annurev.immunol.18.1.767)
C. F. d'Ostiani et al. J. Exp. Med. 191 1661 (2000).
10.1126/science.286.5439.531
P. Tamayo et al. Proc. Natl. Acad. Sci. U.S.A. 96 2907 (1999). (10.1073/pnas.96.6.2907)
We thank T. Golub M. Gaasenbeek and C. Ladd for resources and training for microarray experiments; F. Lewitter and K. Roach for contributions to data analysis and bioinformatics; J. Richmond J. Nau and Q. Feng for advice and reagents; and D. Sabatini G. Fink T. Golub L. Van Parijs M. Albert and R. Khosravi-Far for discussions and critical reading of the manuscript. Supported by grants from the Whitehead Institute Fellows Program Affymetrix Bristol Myers Squibb Millennium Pharmaceuticals Rippel Foundation and Hascoe Foundation.

Dates

Type	When
Created	23 years, 1 month ago (July 27, 2002, 5:54 a.m.)
Deposited	1 year, 7 months ago (Jan. 13, 2024, 4:48 a.m.)
Indexed	1 month ago (Aug. 2, 2025, 12:53 a.m.)
Issued	23 years, 10 months ago (Oct. 26, 2001)
Published	23 years, 10 months ago (Oct. 26, 2001)
Published Print	23 years, 10 months ago (Oct. 26, 2001)

Funders 0

None

BibTeX

@article{Huang_2001, title={The Plasticity of Dendritic Cell Responses to Pathogens and Their Components}, volume={294}, ISSN={1095-9203}, url={http://dx.doi.org/10.1126/science.294.5543.870}, DOI={10.1126/science.294.5543.870}, number={5543}, journal={Science}, publisher={American Association for the Advancement of Science (AAAS)}, author={Huang, Qian and Liu, Dongyu and Majewski, Paul and Schulte, Leah C. and Korn, Joshua M. and Young, Richard A. and Lander, Eric S. and Hacohen, Nir}, year={2001}, month=oct, pages={870–875} }

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