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Science, Vol 294, Issue 5543, 870-875 , 26 October 2001
Abstract of this Article
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Abstract
Full Text
The Plasticity of Dendritic Cell Responses to Pathogens and Their Components
Q. Huang, D. Liu, P. Majewski, L. C. Schulte, J. M. Korn, R. A. Young, E. S. Lander, N. Hacohen

Supplementary Material

Preparation of dendritic cells

Elutriated human monocytes (Advanced Biotechnology Inc.) were grown in RPMI with 10% fetal bovine serum (Life Technologies) supplemented with 1000 U/ml GM-CSF (R&D Systems) and 1000 U/ml IL-4 (R&D Systems) for 7 days in 24 well plates (106 cells in 1 ml medium/well), and fed every 2 days after plating (1).

Stimulation of dendritic cells

On day 7, DC were harvested and aliquoted into 100mm plates at 107 cells/plate and incubated at 37° for 60 min. Pathogens or their components were then added to DC cultures at amounts shown below. Stimulated cells showed mature DC dendrite formation, were less adherent at 24 hours, expressed typical DC markers (cd83, cd86) (Web fig. 4), and stimulated allogeneic T cell proliferation at DC:T ratios of 1:1000-1:10. The following microorganisms were used at the titers shown: E. coli SD54 (ATCC) (5:1 MOI) (kindly provided by J. Nau), Influenza A/PR/8/34 (750 HAU/ml, Hemagglutinin units; the amount of virus needed to infect 50% of the cells was ~ 5-10 HAU/ml, gift of J. Hermann lab), Candida albicans HLC54 (5:1 MOI) (gift of G. Fink lab); and the following components at the concentrations shown: LPS, lipopolysaccharide from E. coli 055:B5 (1 nameg/ml, Sigma L-2880), polyI:C (25 nameg/ml, Pharmacia; endotoxin levels were <0.2 EU/ml, which are not sufficient to induce TNFname expression in DC), mannan from S. cerevisiae (1 mg/ml, Sigma, M 7504). One concern is that the observed pathogen specific responses are due to different titers of each pathogen, rather than to intrinsic differences in pathogen recognition. This is unlikely because many genes within the common response are induced to equal levels by all stimuli, suggesting that some pathways can be engaged equally by all pathogens; the titers used were shown to saturate expression of known maturation markers; all the pathogens were phagocytosed by DC; and in some cases, we repeated microarray measurements with lower titers and concentrations and found similar gene expression profiles (data not shown).


Supplemental Table 1. Summary of donors with pathogens and components

The following table is a summary of the stimuli added to DC from each donor.

DONOR STIMULI
Donor D polyI:C
Donor F E. coli, influenza, LPS, polyI:C
Donor H E. coli, influenza, LPS
Donor I C. albicans
Donor M C. albicans, mannan
Donor O mannan
Donor T E. coli, influenza, C. albicans


RNA preparation and microarray hybridization

At each timepoint (0, 1 hr, 2 hr, 4 hr, 8 hr, 12 hr, 18 hr, 24 hr, 36 hr), 107 cells were harvested and lysed using Trizol (Molecular Research Center). Total RNA was isolated, labeled and prepared for hybridization to HuGeneFL oligonucleotide arrays (Affymetrix) using standard methods (2). Hybridization was carried out overnight with 15 nameg of labeled RNA product, and arrays were scanned on Affymetrix scanners. Measurements were made at multiple timepoints after DC stimulation in order to allow comparison of response levels between six unrelated human donors with variable kinetics and to define different phases in DC activation. Influenza and E. coli responses were always measured in the same donor.

Statistical analysis

Data collection and validation. 1.7 × 106 individual gene measurements were stored, analyzed and visualized using a set of database and analysis tools developed in the lab. Arrays measurements were normalized with a reference array hybridized with sample from the same donor, using the median of the hybridization signals of all genes with P-calls (P-calls according to the Affymetrix software) as a scaling factor. Data for several missing timepoints were interpolated using flanking timepoints. Gene expression profiles were validated by measuring the protein levels of four secreted factors (TNFname, IL12p40, IL10, MCP-1) using standard ELISA measurements which confirmed both the kinetics and the relative induction levels in response to each stimulus (Web fig. 1).

Scoring system. We collected a time series of mRNA fluorescence levels, R={R1, R2, R3,..., Rn}, in DC exposed to each pathogen or compound, and a control series of mRNA levels, C={ C1, C2, C3,..., Cn }, in untreated DC from the same donor. Ri and Ci are steady-state mRNA hybridization measurements ("average difference" in Affymetrix terminology) at the ith timepoint; n is the total number of timepoints. We devised a score, Si=(Ri-nameC)/nameC, to measure significant deviation of the stimulated expression level at one timepoint, Ri from the mean nameCof the control timecourse. By using nameC, which is the standard deviation of the control timecourse, the score penalizes genes with high noise in the media control, thus allowing us to extract the most robust data.

Regulated genes. Upregulated genes were selected according to the following criteria applied at the same time to all three donors: (i) Si>1.2 for name2 consecutive timepoints or (ii) Si>4 for name1 timepoint. Downregulated genes were selected if Si <-1.4 for name4 points; however, since the signal-to-noise was lower than for upregulated genes, we relaxed the filter further and selected the most robust down-regulated genes that passed our filter 2 out of 3 donors and had the same trend in the third donor.

Common regulated genes. Common upregulated genes were selected based on an intersection of the pathogen upregulated genes defined above (i & ii). Common downregulated genes were selected based on Si <-1.2 for name3 points across all pathogens.

Stimulus-specific genes. Fold expression level in response to a stimulus, A, and relative to control is defined as FA=max{L1,L2,...,Ln-1} where Li=geomean{Ri Ri+1}/geomean{Ci Ci+1}. The ratio of fold expression levels for a gene between stimulus A and B is defined as RFAB=FA/FB. Genes that were regulated more strongly by one stimulus (A) than another stimulus (B) were identified in one of two ways: (i) average RFABname2.5 in three donors; or (ii) in three donors, Si>1.4 for name2 points for stimulus A (selects for a gene profile that is significantly different from control timecourse) and Si=1.2 for all points for stimulus B (gene profile closely matches the control timecourse). The final set of stimulus-specific genes (Figs. 1 and 3, stippled circles) were used to describe how the DC response differs biologically for each stimulus. The remaining genes that were regulated in stimulus A but not in stimulus B and did not pass the stimulus-specific filters above were not used in a comparative analysis since they are on the border between the groups of common and stimulus-specific genes.

All filters were used as described above except for:
(1) Two-way comparisons (between DC responses to stimulus A vs. stimulus B) when the responses to A and B were not measured in the same donor for all replicates: (i) Component-pathogen comparisons. All component responses were measured in two donors while all pathogen responses were measured in three donors. To increase the stringency of comparison between component and pathogen, we required that the average RFABname2.5 (as for all other comparisons) and that FA/FBname2 for one experiment in which the component and pathogen are measured in the same batch of DC.
(ii) C. albicans-pathogen comparisons. Since the same batch of DC were exposed only in one experiment (donor T) to all the pathogens (C. albicans, E. coli and influenza), we increased the stringency of any pathogen comparison to C. albicans by requiring that the average RFABname2.5 and that FA/FBname2 for the experiment in which all the pathogen responses were measured (donor T).
(2) Regulated genes for component responses, which were measured in two donors, require a more stringent filter: Upregulated genes were selected according to the following criteria for one experiment: (i) Si>2 for name2 consecutive timepoints or (ii) Si>1.2 for name3 consecutive timepoints or (iii) Si>5 for name1 timepoint; the same criteria were applied to an independent experiment from a second donor, except (i) was replaced with a less stringent filter, Si>1.4 for name2 points, to take into account variations in level of expression between donors. Downregulated genes were selected if Si <-1.4 for name2 points.

Temporal clustering

A self-organizing map algorithm (3) was used to cluster genes together based on the similarity of their temporal expression profiles. We used this procedure to aid us in classifying genes into six basic groups: three major groups which consist of genes that are expressed in an early, middle or late phase of the timecourse; and for each of these groups, the genes are further divided up into those that are expressed transiently or in a sustained fashion (Fig. 2A).

Functional categories

We also assigned each of the regulated genes into functional categories (e.g. chemokines, glycolysis, etc.) according to the public databases. We verified and refined our assignment of functional groups by comparing to the Proteome annotated database of genes, Human PSD(tm) (kindly provided through a collaboration with Proteome, Inc).

Neutrophil migration

Neutrophil isolation and migration assays were done with standard techniques (4). Directed neutrophil migration was measured using 96-well chambers with filters (Neuroprobe). 20,000 neutrophils were fluorescently labelled with PKH26 (Sigma) and placed on top of the filter; DC supernatants were placed below (1:10 dilution). After incubating for 30 min at 37°C and 10 min at 4°C, neutrophils were counted on the bottom of each well.

References
1. M. Cella et al., J. Exp. Med. 189, 821 (1999).
2. T. R. Golub et al., Science 286, 531 (1999).
3. P. Tamayo et al., Proc. Natl. Acad. Sci. U.S.A. 96, 2907 (1999).
4. J. E. Coligan et al., Eds., Current Protocols in Immunology (Wiley, 1999).


Supplemental Figure 1. mRNA and protein expression levels for several cytokines and chemokines. (A) TNFa. Left panels are hybridization fluorescence levels from Affymetrix microarrays (average difference). Right panels are standard ELISA measurements (R&D Systems) of protein levels from the supernatant of the same DC incubated with different pathogens or components (see legend on right). (B) IL-12/p40. (C) mcp-1. (D) IL-10.


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Supplemental Figure 2. Comparison of E. coli-regulated and component-regulated gene expression in human monocyte-derived dendritic cells. (A) Right panel, Overlapping sets of E. coli- and LPS regulated genes(see methods). The number of the pathogen-specific genes are shown inside the stippled circles (see methods). Some stimulus-specific genes are also found in the common group but are much more strongly regulated in one stimulus that in others and are used to define stimulus-specific properties of DC. Left panel, representation of mRNA expression levels at 0, 1, 2, 4, 8, 12, 24 hours in response to E.coli and LPS. Each gene is represented by a single row of colored bars, and each time point is represented by a single column. Color bars represent the ratio of hybridization measurements between corresponding timepoints in the pathogen and control medium profiles, according to the scale shown. Genes are placed in groups corresponding to pair-wise overlaps shown in accompanying Venn diagrams. From top to bottom: E. coli- but not LPS-regulated genes; common regulated genes; LPS but not E. coli regulated genes. The vertical grey bar on the right marks stringent stimulus-specific genes corresponding to the stippled circles in the Venn diagram. (B) Gene profiles and overlap of E.coli and mannan. (C) Gene profiles and overlaps for E.coli and dsRNA.


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Supplemental Figure 3. Comparison of pathogen and component-regulated gene expression in human monocyte-derived dendritic cells. (A) Gene profiles and overlap of C. albicans and mannan. (B) Influenza and dsRNA. All conventions are as in Supplementary Figure 2.


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Supplemental Figure 4. FACS analysis of DC preparations. (A) cd86 (B7-2) staining of untreated DC or DC treated with LPS or polyI:C. (B) cd83 staining of untreated DC or DC treated with LPS. (C) cd14 staining of monocytes, untreated DC or DC treated with LPS. Dendritic cells have no cd14 expression and are off-scale to the left of the x-axis.


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Supplemental Figure 5. Differential effects of pathogens on neutrophil chemotaxis. Migration of neutrophils (in a chemotaxis chamber) toward conditioned cell culture medium collected from DC exposed to control medium, influenza or E. coli for different times. Results were reproduced in two donors in five independent experiments.


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Abstract of this Article
Full Text of this Article

Volume 294, Number 5543, Issue of 26 Oct 2001, p. 870.
Copyright © 2004 by The American Association for the Advancement of Science. All rights reserved.

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