Gene expression profiles of peripheral blood leukocytes after endotoxin challenge in humans.

Abstract

To define gene expression profiles that occur during the initial activation of human innate immunity, we administered intravenous endotoxin (n = 8) or saline (n = 4) to healthy subjects and hybridized RNA from blood mononuclear cells (0, 0.5, 6, 24, 168 h) or whole blood (0, 3, 6, 24, 168 h) to oligonucleotide probe arrays. The greatest change in mononuclear cell gene expression occurred at 6 h (439 induced and 428 repressed genes, 1% false discovery rate, and 50% fold change) including increased expression of genes associated with pathogen recognition molecules and signaling cascades linked to receptors associated with cell mobility and activation. Induced defense response genes included cytokines, chemokines, and their respective receptors, acute-phase transcription factors, proteases, arachidonate metabolites, and oxidases. Repressed defense response genes included those associated with co-stimulatory molecules, T and cytotoxic lymphocytes, natural killer (NK) cells, and protein synthesis. Gene expression profiles of whole blood had similar biological themes. Over 100 genes not typically associated with acute inflammation were differentially regulated after endotoxin. By 24 h, gene expression had returned to baseline values. Thus the inflammatory response of circulating leukocytes to endotoxin in humans is characterized by a rapid amplification and subsidence of gene expression. These results indicate that a single intravascular exposure to endotoxin produces a large but temporally short perturbation of the blood transcriptome.

Full text

Page 1

doi:10.1152/physiolgenomics.00192.2005
25:203-215, 2006. First published 10 January 2006;
Physiol. Genomics
Shelhamer, Robert L. Danner and Anthony F. Suffredini
H.Cintron, Carolea Logun, Margaret Tropea, Sameena Khan, Debra Reda, James
Shefali Talwar, Peter J. Munson, Jennifer Barb, Carmen Fiuza, Anadel Pilar
after endotoxin challenge in humans
Gene expression profiles of peripheral blood leukocytes
You might find this additional info useful...
for this article can be found at:
http://physiolgenomics.physiology.org/content/suppl/2006/03/15/00192.2005.DC1.html
Supplemental material
49 articles, 23 of which can be accessed free at:
http://physiolgenomics.physiology.org/content/25/2/203.full.html#ref-list-1
This article cites

10 other HighWire hosted articles, the first 5 are:
Plasma Levels of Soluble CD14 Independently Predict Mortality in HIV Infection
This article has been cited by

[PDF] [Full Text] [Abstract]
, March , 2008; 65 (3): 211-214.
Occup Environ Med
P Kierulf
L I B Sikkeland, M Skogstad, R Øvstebø, B Brusletto, K B F Haug, J Kongerud, W Eduard and
Circulating lipopolysaccharides in the blood from ''bioprotein'' production workers

[PDF] [Full Text] [Abstract]
, June , 2010; 42 (1): 5-19.
Physiol. Genomics
Panagiota T. Foteinou, Steve E. Calvano, Stephen F. Lowry and Ioannis P. Androulakis
Multiscale model for the assessment of autonomic dysfunction in human endotoxemia

[PDF] [Full Text] [Abstract]
, December 31, 2010; 285 (53): 41391-41401.
J. Biol. Chem.
Zhiyong Zhang, Stephen F. Lowry, Leonard Guarente and Beatrice Haimovich
Roles of SIRT1 in the Acute and Restorative Phases following Induction of Inflammation

[PDF] [Full Text] [Abstract]
, January 20, 2011; .
J Infect Dis.
SMART Study Group
Jason M. Brenchley, Steven G. Deeks, Irini Sereti, Daniel C. Douek and for the INSIGHT
Nixon, Court Pedersen, Kiat Ruxrungtham, Sharon R. Lewin, Sean Emery, James D. Neaton,
Netanya G. Sandler, Handan Wand, Annelys Roque, Matthew Law, Martha C. Nason, Daniel E.
Plasma Levels of Soluble CD14 Independently Predict Mortality in HIV Infection

[PDF] [Full Text] [Abstract]
, March 15, 2011; 203 (6): 780-790.
J Infect Dis.
Jason M. Brenchley, Steven G. Deeks, Irini Sereti and Daniel C. Douek
Nixon, Court Pedersen, Kiat Ruxrungtham, Sharon R. Lewin, Sean Emery, James D. Neaton,
Netanya G. Sandler, Handan Wand, Annelys Roque, Matthew Law, Martha C. Nason, Daniel E.
including high resolution figures, can be found at:Updated information and services
http://physiolgenomics.physiology.org/content/25/2/203.full.html
can be found at:
Physiological Genomics
about Additional material and information
http://www.the-aps.org/publications/pg
This infomation is current as of May 18, 2011.

the American Physiological Society. ISSN: 1094-8341, ESSN: 1531-2267. Visit our website at http://www.the-aps.org/.
July, and October by the American Physiological Society, 9650 Rockville Pike, Bethesda MD 20814-3991. Copyright © 2006 by
techniques linking genes and pathways to physiology, from prokaryotes to eukaryotes. It is published quarterly in January, April,
publishes results of a wide variety of studies from human and from informative model systems with
Physiological Genomics
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 2

Gene expression profiles of peripheral blood leukocytes after endotoxin
challenge in humans
Shefali Talwar,1Peter J. Munson,2Jennifer Barb,2Carmen Fiuza,1
Anadel Pilar Cintron,1Carolea Logun,1Margaret Tropea,1Sameena Khan,1
Debra Reda,1James H. Shelhamer,1Robert L. Danner,1and Anthony F. Suffredini1
1Critical Care Medicine Department, Clinical Center, and2Mathematics and Statistical Computing
Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, Maryland
Submitted 29 July 2005; accepted in final form 5 January 2006
Talwar, Shefali, Peter J. Munson, Jennifer Barb, Carmen
Fiuza, Anadel Pilar Cintron, Carolea Logun, Margaret Tropea,
Sameena Khan, Debra Reda, James H. Shelhamer, Robert L.
Danner, and Anthony F. Suffredini. Gene expression profiles of
peripheral blood leukocytes after endotoxin challenge in humans.
Physiol Genomics 25: 203–215, 2006. First published January 10,
2006; doi:10.1152/physiolgenomics.00192.2005.—To define gene ex-
pression profiles that occur during the initial activation of human
innate immunity, we administered intravenous endotoxin (n ? 8) or
saline (n ? 4) to healthy subjects and hybridized RNA from blood
mononuclear cells (0, 0.5, 6, 24, 168 h) or whole blood (0, 3, 6, 24,
168 h) to oligonucleotide probe arrays. The greatest change in mono-
nuclear cell gene expression occurred at 6 h (439 induced and 428
repressed genes, 1% false discovery rate, and 50% fold change)
including increased expression of genes associated with pathogen
recognition molecules and signaling cascades linked to receptors
associated with cell mobility and activation. Induced defense response
genes included cytokines, chemokines, and their respective receptors,
acute-phase transcription factors, proteases, arachidonate metabolites,
and oxidases. Repressed defense response genes included those asso-
ciated with co-stimulatory molecules, T and cytotoxic lymphocytes,
natural killer (NK) cells, and protein synthesis. Gene expression
profiles of whole blood had similar biological themes. Over 100 genes
not typically associated with acute inflammation were differentially
regulated after endotoxin. By 24 h, gene expression had returned to
baseline values. Thus the inflammatory response of circulating leu-
kocytes to endotoxin in humans is characterized by a rapid amplifi-
cation and subsidence of gene expression. These results indicate that
a single intravascular exposure to endotoxin produces a large but
temporally short perturbation of the blood transcriptome.
innate immunity; inflammation; leukocyte transcriptome
SEPSIS IS A SYSTEMIC INFLAMMATORY disorder induced by infec-
tion and, when severe, is accompanied by shock with organ
failure. It is a major cause of morbidity and death in critically
ill patients (32). While the host inflammatory response is
necessary to localize and resolve an infection, it has a central
pathogenic role in the development and severity of sepsis
syndromes (3). Therapy of septic shock is based on infection
control, hemodynamic resuscitation, and attempts to modify
the inflammatory response. Yet in the latter case, treatment
directed at a single mediator or inflammatory pathway has met
with only limited success in improving survival in sepsis (3, 4,
17, 35). Major challenges remain in understanding the mech-
anisms that contribute to these processes.
The pathogenesis of sepsis is directly related to innate
immunity, which encompasses the immediate host inflamma-
tory responses that result from exposure to microbial compo-
nents (5). The rapid immune responses are initiated by con-
served microbial structures that activate pattern recognition
receptors on cell surfaces and in the circulation (e.g., endo-
toxin, Toll-like receptors, and lipopolysaccharide-binding pro-
tein, respectively) (6, 33). These interactions result in cell
activation, the release of inflammatory molecules, and the
recruitment of inflammatory cells to sites of infection (37).
Investigators have administered the gram-negative bacterial
wall component endotoxin to healthy human subjects to learn
more about the mechanisms associated with sepsis (48). This
model results in physiological responses that are archetypal of
innate immunity, cell activation and inflammatory mediator
release that cause fever, leukocytosis, tachycardia, tachypnea,
and decreased blood pressure, findings similar to the early
signs of infection in patients (1, 41, 46). To further characterize
the complex phenomena associated with this common bacterial
product, we studied differential gene expression of peripheral
blood from healthy subjects challenged with intravenous en-
dotoxin using oligonucleotide gene arrays. Oligonucleotide
arrays have been used to profile the complex gene networks
associated with normal physiology and disease (11, 44, 45).
We have previously shown (42) that some acute-phase proteins
persist in the blood for 7–10 days after intravenous endotoxin
challenge, and we hypothesized that alterations in the tran-
scriptome may persist for several days mirroring this acute
inflammatory response.
We show that the administration of a single dose of intra-
venous endotoxin to humans leads to a rich profile of gene
expression changes in blood. These include the induction of
genes associated with pattern recognition molecules, intracel-
lular signaling and transcription, cell mobility, and defense
function. T lymphocyte-associated genes were repressed, and
many genes not previously associated with endotoxin-induced
inflammation were differentially regulated during this re-
sponse. Notably, these alterations in gene expression were
rapidly extinguished within 24 h, and scant residua of this
response were detected at 7 days.
METHODS
Materials
Vacutainer CPT cell preparation tubes for isolation of peripheral
blood mononuclear cells, mouse anti-human CD14-PE, CD45-PerCP,
Article published online before print. See web site for date of publication
(http://physiolgenomics.physiology.org).
Address for reprint requests and other correspondence: A. F. Suffredini,
Bldg. 10, Rm. 7D-43, CCMD/CC/NIH, 10 Center Dr., Bethesda, MD 20892-
1662 (e-mail: asuffredini@mail.cc.nih.gov).
Physiol Genomics 25: 203–215, 2006.
First published January 10, 2006; doi:10.1152/physiolgenomics.00192.2005.
203
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 3

CD4-FITC, CD8-FITC, CD69-PE, CD25-PE, CD3-PerCP, tricolor
CD3-FITC/19-PE/45-PerCP,tricolor
CD45-PerCP, tricolor CD3-PerCP/4-FITC/8-PE, IgG-PE, and IgG-
FITC antibodies were obtained from Becton Dickinson (Franklin
Lakes, NJ). RLT buffer, RNeasy Midi and Mini kits, and DNase 1
were purchased from Qiagen (Valencia, CA). PAXgene blood RNA
tubes and PAXgene Blood RNA Kit were purchased from PreAna-
lytiX, Qiagen. T7-d(T)24primer was obtained from Genset (La Jolla,
CA). SuperScript Double Stranded cDNA Synthesis Kit was from
Invitrogen (Rockville, MD). Phase Lock Gel was obtained from
Eppendorf (Westbury, NY), and phenol-chloroform-isoamyl alcohol
(25:24:1) was purchased from Invitrogen (Carlsbad, CA). HighYield
RNA Transcript Labeling Kit was purchased from Enzo Diagnostic
(Farmingdale, NY). GeneChip Sample Cleanup Module was obtained
from Affymetrix (Santa Clara, CA). Human Multiplex Antibody Bead
Kits for Luminex were purchased from BioSource International
(Camarillo, CA).
CD3-FITC/CD16&56-PE/
Human Subjects
Six men and four women (20–45 yr; mean ? SE, 30 ? 2 yr) in
good health participated in the study. None used tobacco products,
and all had normal screening blood tests, electrocardiograms, and
chest radiographs. Informed written consent was obtained from each
subject. Human experimental guidelines of the United States Depart-
ment of Health and Human Services were followed, and the study was
approved by the Institutional Review Board of the National Institute
of Allergy and Infectious Diseases (Bethesda, MD). Eight subjects
were given intravenous endotoxin [4 ng/kg, Escheria coli O:113,
Clinical Center Reference Endotoxin, National Institutes of Health
(NIH), Bethesda, MD], and four subjects were given intravenous
saline alone. This dose of endotoxin is safe and elicits a broad variety
of physiological responses that are similar to the syndrome of sepsis
(41, 46, 48). Two of the four subjects given saline participated in the
endotoxin portions of the study, separated by at least 6 wk. Blood was
drawn from either radial arterial catheters or by venipuncture after the
endotoxin or saline challenge. Temperature was monitored with tym-
panic membrane thermometers, heart rate by continuous electrocar-
diogram, and arterial pressure by arterial catheter or cuff pressure.
Automated total and differential blood cell counts were determined
(Coulter). The effects of endotoxin were studied in two different cell
populations: peripheral blood mononuclear cells (PBMC) and whole
blood.
Blood Cell Preparation and Total RNA Isolation
PBMC. After endotoxin or saline challenge, blood was drawn at 0,
0.5, 6, 24, and 168 h. These time points were chosen to assess
responses before and immediately after the lymphopenia and mono-
cytopenia that occur with intravenous endotoxin (47). To minimize in
vitro manipulations that might introduce bias into expression profiles
(12, 19), blood was collected directly in cell preparation tubes con-
taining sodium citrate and Ficoll Hypaque density fluid (Vacutainer
CPT), placed on ice, and centrifuged within 30 min (2,200 g, 8°C for
30 min). The PBMC layer was removed, washed with cold PBS, and
centrifuged (900 g, 8°C for 10 min). Contaminating red blood cells
were lysed with ammonium chloride lysing buffer. Sample quality
was confirmed by a differential blood smear, and an aliquot of cells
was placed aside for surface marker analysis using flow cytometry.
After a washing in PBS, the cells were lysed with RLT buffer,
homogenized using a syringe and 20-gauge needle, and then stored at
?80°C. The process from sample acquisition to cell lysate was
performed within 90 min for each sample to minimize the affects of
processing on the in vivo expression profile. After all time points per
subject were acquired, total RNA was extracted as per RNeasy Midi
protocol (Qiagen). The quality of the total RNA was assessed by
visualization of intact 18S and 28S ribosomal RNA bands using a
1.2% formaldehyde agarose gel (Ambion, Austin, TX) stained with
Sybr Green II (Molecular Probes, Eugene, OR). The 260/280 ratio of
all samples was between 1.8 and 2.0. Baseline samples (0 h) revealed
a negligible number of neutrophils. At 6 h, neutrophil contamination
of the PBMC preparations was ?10% of the total cells. Our previous
work has shown that, because of the low amount of RNA present in
neutrophils, this amount of contamination would contribute minimally
to the gene profiles of the PBMC (28).
Whole blood cells. In four subjects challenged with intravenous
endotoxin, samples of whole blood cells were collected at 0, 3, 6, 24,
and 168 h in PAXgene blood RNA tubes. These time points were
chosen to sample whole blood immediately after the release of
cytokines and after the onset of monocytopenia. In addition, PBMC
were collected in these same subjects at 0, 6, and 24 h. Whole blood
cell RNA was isolated. Total RNA was extracted and treated with
DNase 1 as per PAXgene Blood RNA Kit protocol with the following
modifications: after 2 h of incubation at room temperature, blood
samples were kept for a minimum of 24 h at 4°C, and total RNA was
precipitated overnight with 3 M sodium acetate and 100% ethanol. All
samples were processed within 72 h from time of collection.
PBMC and Whole Blood Cell Total RNA Hybridization to
Oligonucleotide Probe Arrays
Double-stranded cDNA was synthesized from total RNA (5–20
?g) using 7-d(T)24 primer and SuperScript Double-Stranded cDNA
Synthesis Kit. cDNA was purified by Phase Lock Gel-phenol-chloro-
form extraction followed by ethanol precipitation. Biotin-labeled
cRNA was prepared by in vitro transcription using HighYield RNA
Transcript Labeling Kit followed by fragmentation with 5? fragmen-
tation buffer (200 mM Tris-acetate, pH 8.1, 500 mM potassium
acetate, 150 mM magnesium acetate) at 94°C for 35 min. Fragmented
cRNA (10 ?g) was hybridized to Affymetrix Hu95Av2 oligonucleo-
tide probe arrays for 16 h at 45°C. After removal of hybridization
fluid, the arrays were washed and stained with streptavidin-phyco-
erythrin (SAPE), and signal was amplified by anti-streptavidin anti-
body using Affymetrix Fluidics Station 400. Probe set signals were
measured using Agilent GeneArray Scanner (Affymetrix).
Validation of Gene Expression Using Real-Time PCR
Real-time PCR (RT-PCR) was used to validate the microarray
results for PBMC data sets (TaqMan PCR detection; Applied Biosys-
tems, Rockville, MD). Probes and primers for 12 target sequences
were designed using Primer Express computer software (Applied
Biosystems) or purchased (Applied Biosystems) (see Supplemental
Table S1; available at the Physiological Genomics web site).1Total
RNA from the PBMC of four subjects was extracted as above, treated
with DNase 1, and reverse transcribed to cDNA using random
hexamers and High Capacity cDNA Archive Kit as per the manufac-
turer’s instructions (Applied Biosystems). The gene of interest was
then amplified and quantified using TaqMan Universal PCR master
mix and TaqMan probe and primers on ABI PRISM 7900HT Se-
quence Detection System (Applied Biosystems). RNase P was used as
internal control (Applied Biosystems). The standard curve method
was used to quantify the gene of interest and then normalized to
RNase P. Final results were expressed as fold change, comparing 6
with 0 h after intravenous endotoxin.
Flow Cytometry of Isolated PBMC
Cell surface markers for identifying different cell populations were
analyzed at times of 0 and 6 h after endotoxin challenge. The PBMC
preparations were evaluated for percentage of T cells, B cells, natural
killer (NK) cells, and monocytes. T lymphocytes were analyzed for
1The Supplemental Material for this article (Supplemental Tables S1–S5) is
available online at http://physiolgenomics.physiology.org/cgi/content/full/
00192.2005/DC1.
204
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 4

CD4 and CD8 subsets and for markers of early and late activation.
Cells were resuspended in PBS, incubated with mouse anti-human
antibody for 30 min at 4°C, washed with PBS, and fixed with 1%
formaldehyde. Monocyte and lymphocyte differential counts were
determined by staining cells with CD14-PE and CD45-PerCP.
CD14-PE bright population was back-gated to light scatter to quantify
monocyte percentage, and the remaining cells were considered lym-
phocytes. The percentage of T cells, B cells, and NK cells was
determined by staining cells with tricolor CD3-FITC/19-PE/45-PerCP
or tricolor CD3-FITC/CD16&56-PE/CD45-PerCP, gating on CD45-
PerCP. T lymphocyte subset (CD4 and CD8) percentages were iden-
tified using tricolor CD3-PerCP/CD4-FITC/CD8-PE stain, gating on
CD3-PerCP. Finally, labeling with CD3-PerCP/CD4-FITC/CD69-PE,
CD3-PerCP/CD8-FITC/CD69-PE, CD3-PerCP/CD4-FITC/CD25-PE,
or CD3-PerCP/CD4-FITC/CD25-PE identified early and late activa-
tion of CD4 and CD8 cells. Gated events (2,000) were collected using
FACScan system and analyzed with CELLQuest software (Becton
Dickinson).
Measurement of Blood Inflammatory Protein Markers
Serum samples for tumor necrosis factor (TNF)-?, interleukin
(IL)-1?, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, interferon (IFN)-?,
regulated upon activation, normal T cell expressed, and secreted
(RANTES), macrophage inflammatory protein (MIP)-1?, MIP-1?,
monocyte chemotactic protein (MCP)-1, eotaxin, granulocyte macro-
phage colony-stimulating factor (GM-CSF), and vascular endothelial
growth factor (VEGF) were measured at 0, 3, 6, and 24 h using a
multiplex bead-based assay (Human Multiplex Antibody Bead Kits
for Luminex) according to the manufacturer’s recommendations. The
samples were measured using the antibody bead mix in duplicate with
a biotinylated detection antibody followed by streptavidin-phyco-
erythrin. The plate was read using the Luminex XYP platform
(Luminex, Austin, TX), and data were collected for 100 beads per
cytokine from each well. The raw data (mean fluorescent intensity)
were processed on Masterplex Quantitation software (MiraiBio, Al-
ameda, CA) to obtain concentration values.
Statistical Analysis: Data Transformation
The average difference (AD) values (Affymetrix Microarray Suite
4.0) for the oligonucleotide arrays were stored in the NIH Laboratory
Information Management System (LIMS) database and retrieved,
transformed, and analyzed with the use of the Mathematical and
Statistical Computing Laboratory (MSCL) Analyst’s Toolbox (http://
abs.cit.nih.gov/MSCLtoolbox/) written by P. J. Munson and J. Barb
in the JMP scripting language (SAS Institute, Cary, NC). Values (AD)
were standardized and transformed using the Symmetric Adaptive
Transform, which yields quantile-normalized, homogeneous variance
scale intensity values, termed S-AD (16, 28). A consistency test was
applied to identify subjects with a consistent change in the S-AD
across all treated subjects. The analysis specified a 1% false discovery
rate for each set of detected genes found in the PBMC and whole
blood (43). The list was further refined by requiring that the relative
change between late time points compared with time baseline (fold
change) be at least 50%. To eliminate genes that were at or below the
stated detection limits for this assay, an average AD value ?20 was
required in at least one of the two compared groups.
The transformed data matrix [samples (columns) by genes (rows)]
was subjected to principal components analysis to visualize the
relative location of chips in a low-dimensional space allowing for
detection of outliers or other relevant patterns. Genes were annotated
using the Gene Ontology (GO) database (http://www.geneontology.
org) and the GO-Significant Collection of Annotations (SCAN) pro-
gram (http://abs.cit.nih.gov/goscan/) for assessing significantly
overrepresented annotation terms. GO-SCAN presents an interactive
table of terms and permits drill-down into the supporting expression
data. Overrepresentation of the annotation category was determined
using a one-sided Fishers exact test. The annotation terms were then
analyzed using the GO-MAP program (http://abs.cit.nih.gov/
goscan/), which performs a 2-D hierarchical clustering of terms and
genes to group possibly redundant annotations and corresponding
genes into blocks that can be presented graphically. Groups of
similarly annotated genes may then be studied together in relation to
their expression results. One hundred twelve genes of the final gene
list have been reported in part as a comparison population describing
gene expression in patients with stable sickle cell anemia (28). The
entire data set of the above investigation has been submitted to the
National Center for Biotechnology Information Gene Expression
Omnibus (NCBI GEO; http://www.ncbi.nlm.nih.gov/projects/geo/
index.cgi), accession number GSE3026.
RESULTS
Systemic Responses to Endotoxin
All subjects given endotoxin developed mild to moderate
degrees of malaise, headache, and fever (0 h, 37.1 ? 0.1°C,
and 3 h, 39.03 ? 0.2°C) tachycardia (0 h, 62 ? 5 beats/min,
and 3 h, 96 ? 4 beats/min) and a decrease in mean arterial
pressure (0 h, 90 ? 3 mmHg, and 5 h, 74 ? 3 mmHg)
(maximum change from baseline, all P ? 0.01, paired t-test).
Saline-challenged subjects had similar baseline vital signs with
no significant changes during the study period. Within 1 h, total
leukocyte counts reached their nadir due to margination of cells
to activated vascular endothelium (31, 39, 47, 51). This was
followed by a rapid rise in total leukocyte counts composed
primarily of neutrophils, while mononuclear cells were de-
creased in number compared with baseline. At 6 h, the number
of mononuclear cells began to rise and returned toward normal
at 24 h (Table 1). Blood cytokines (TNF-?, IL-1?, IL-6, IL-8,
IL-10, MCP-1, MIP-1? and -?) rose at 3 h and returned to
baseline values by 6–24 h (Table 2). These eight cytokines and
chemokines have been described in normal subjects given
endotoxin compared with saline in previous publications (re-
viewed in Ref. 48). In these previous studies, no changes occur
from baseline in the saline-challenged subjects.
Cell Components of Mononuclear Cell Preparations
The proportion of lymphocytes and monocytes present after
density centrifugation separation at 0 and 6 h is summarized in
Fig. 1. Compared with baseline, endotoxin administration re-
sulted in the percentage of lymphocytes falling by almost 50%
Table 1. Changes in peripheral blood leukocytes after
intravenous endotoxin administration
0 h6 h24 h168 h
Endotoxin
Total cells,
?109cells/l
Neutrophils, %
Lymphocytes, %
Monocytes, %
4.65?0.55
55.4?3.3
34.05?3.6
6.1?1.5
11.97?0.85
92.5?1.4
3.7?0.7
3.3?0.7
7.69?0.50
68.6?2.9
22.41?2.0
6.8?1.0
7.14?0.63
63.6?2.2
28.6?2.0
5.0?0.7
Saline
Total cells,
?109cells/l
Neutrophils, %
Lymphocytes, %
Monocytes, %
5.22?0.35
52.9?2.9
36.4?1.9
7.9?1.0
5.15?0.41
49.2?3.2
41.5?2.3
7.4?0.8
5.90?0.19
54.9?2.3
36.1?2.9
7.2?1.2
5.55?0.36
52.6?2.0
37.7?2.5
7.5?1.3
Values are means ? SE.
205
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 5

and the percentage of monocytes increasing by threefold at 6 h.
The percentage of T lymphocytes and NK cells remained the
same, while the proportion of B cells increased at 6 h (Fig. 1,
inset). The percentage of CD3? lymphocytes at 6 h expressing
CD4 and CD8 surface markers did not change from baseline (0
h: CD4 58.0 ? 2.8%; CD8, 35.0 ? 3.2%). CD4? and CD8?
cells expressing an early activation marker (CD69) increased at
6 h (CD4?69? 0 h, 0.8 ? 0.3%, and 6 h, 5.0 ? 1.7%, P ?
0.035; and CD8?69? 0 h, 1.9 ? 0.7%, and 6 h, 7.6 ? 3.1%,
P ? 0.07, paired t-test). No changes in CD4?69? or
CD8?69? cells occurred in the control subjects, suggesting
that cell processing was not associated with induction of this
early marker of lymphocyte activation. The percentage of
CD4? or CD8? cells expressing a late marker of activation
(CD25) was unchanged at 6 h (0 h: CD4?25?, 18.1 ? 4.4%;
CD8?CD25?, 1.4 ? 0.4%).
Differential Gene Expression in PBMC After Endotoxin
Endotoxin is cleared from the blood within 30 min after
intravenous administration, suggesting that many of its down-
stream effects are due to secondary mediators that amplify the
initial host response to this bacterial component (50). A major
source of TNF, an important secondary mediator that enhances
the host response to endotoxin, is from the liver (23, 34). The
resultant inflammatory milieu in blood has profound effects on
genes associated with both the afferent and efferent arms of
innate immunity. At 6 h, ?800 genes were differentially
regulated; 439 genes were induced, and 428 genes were re-
pressed compared with baseline (Fig. 2A and Supplemental
Table S2A). GO categories that were significantly (P ? 0.01)
represented among these genes are depicted by GO-MAPs
found in Supplemental Table S2, B (induced genes) and C
(repressed genes). Twelve genes were differentially regulated
at other time points: 30 min (4 induced), 24 h (5 induced and
2 repressed), and 168 h (1 induced). Eight genes were altered
in control subjects, of which only two genes (Hgb-? and
AP1G2) overlapped with the endotoxin-associated gene list
and were removed from further analysis.
Table 2. Acute-phase cytokines in serum after intravenous
endotoxin challenge
0 h3 h 6 h24 h
P Value
TNF?
IL-1?
IFN?
IL-2
IL-4
IL-5
IL-6
IL-8
IL-10
MCP-1
MIP1?
MIP1?
RANTES
Eotaxin
VEGF
94?1
35?6
54?32
130?24
82?2
52?0
0
26?1
87?0
303?74
261?1
100?46
1,717?71
188?22
306?30
454?100
197?32
55?28
79?3
84?3
52?1
3,155?1,054
1,023?170
326?41
18,179?2,078
581?28
13,696?1,624
1,997?175
252?53
342?36
98?2
49?10
50?27
130?23
83?3
52?0
24?24
206?82
94?2
5,218?2,794
300?15
2,118?570
1,833?90
291?81
325?22
94?1
37?4
55?35
133?25
82?3
51?0
0
36?4
87?0
452?58
266?2
207?89
1,933?114
272?47
300?23
?0.0001
?0.0001
NS
NS
NS
NS
?0.0001
?0.0001
?0.0001
?0.0001
?0.0001
?0.0001
NS
NS
NS
Serum samples (means ? SE) for the following were measured at baseline
(0 h) and 3, 6, and 24 h using a multiplex bead-based assay and analyzed by
ANOVA for time effect: tumor necrosis factor (TNF)?; interleukin (IL)-1?, -2,
-4, -6, -8, and -10; interferon (IFN)?; regulated on activation, normal T cell
expressed and secreted (RANTES); macrophage inflammatory protein
(MIP)1? and -1?; monocyte chemotactic protein (MCP)-1; eotaxin; and
vascular endothelial growth factor (VEGF). NS, not significant.
Fig. 1. Proportion of lymphocytes and monocytes present after
density centrifugation separation at 0 and 6 h. Compared with
baseline, endotoxin administration resulted in the percentage of
lymphocytes falling by almost 50% and the percentage of mono-
cytes increasing by 3-fold at 6 h. Inset: percentage of T lymphocytes
and natural killer (NK) cells remained the same while the propor-
tion of B cells increased at 6 h.
206
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 6

Afferent Limb of Innate Immunity
The afferent limb of innate immunity encompasses those
responses necessary for the host to recognize and to activate
inflammatory responses to a pathogen (Table 3). Endotoxin
administration was associated with the induction of cell surface
receptor genes whose products enhance cell recognition of
microbial signals [TLR1 and -2, CD14, FPRL1, and scavenger
receptors (MARCO)]. Soluble pathogen-recognition molecules
and their respective receptors or receptor components were
induced [i.e., bactericidal permeability-increasing protein, pro-
perdin P factor, C1q receptor 1, C3a receptor 1, and C (3b/4b)
receptor 1]. The mRNA of immune complex receptors (Fc-?
receptor I and II) and leukocyte immunoglobulin-like receptors
(LILRA3, LILRB2, LILRB3, and LILRB4) was upregulated.
The latter are associated with major histocompatibility com-
plex (MHC) class I antigens and may result in a stimulatory
(LILRA3) or inhibitory cascade (LILRB2, -3, -4). These re-
sponses suggest that the mononuclear cells are primed to
respond to further microbial component exposure.
Simultaneously, major changes occur in the induction of
genes associated with intracellular signaling cascades: G pro-
tein-linked receptors (protein kinase C or PRKCD), MAPKs
(MAPK14 or p38), p21 activated kinase 2 (PAK2), receptor
tyrosine kinases [phosphatidylinositol 3-kinase (PI3K), GT-
Pase], and receptor tyrosine kinase-associated genes (Src, JAK,
Ras, Rho). These pathways are linked to receptor families that
affect cell mobility, proliferation, activation, and effector func-
tion.
Efferent Limb of Innate Immunity
The activation of host inflammatory cells initiates the effer-
ent limb of innate immunity (Table 3). This results in the
release of inflammatory molecules and changes in cell struc-
tural components to enhance association with activated endo-
thelium and migration to a nidus of infection. The activation of
the mononuclear cells results in changes in cytoskeleton
(MARCKS, actin), membrane and ion channel genes (aqua-
porin 9), and genes that enhance cell motility (uPAR, L-
selectin or CD63, CD11b or complement receptor type 3,
?-subunit). Anti-proteases (SERPINA1 and -B1) and disinte-
grins with domains that have potential for adhesion and met-
alloprotease activity are upregulated (ADAM8 and -9). Imme-
diate anti-pathogen responses include the induction of micro-
bicidal oxidases [CYBA (p22-phox), CYBB (gp91-phox)] and
their regulators [superoxide dismutase (SOD)]. These efferent
responses are modulated by the induction of cytokines (IL-
1Ra), cytokine and chemokine receptors (INFGR2, IL-10R-?,
IL-17R, CCR1, CCR2), growth factors (VEGF, ECGF1), and
growth factor receptors (CSF2RA and -B, BST1 and -2).
Arachidonate metabolism is potentiated by the upregulation of
platelet-activating factor acetylhydrolase (PLA2G7) and leu-
kotriene B4 receptor and the induction of arachidonate 5-li-
poxygenase-activating protein (ALOX5AP), which, with 5-li-
poxygenase (ALOX5), is required for leukotriene synthesis.
Genes associated with cell stress are upregulated [heat shock
(HS) 90-kDa protein 1?; HS 70-kDa protein 1A, 1B, and 5; HS
Fig. 2. A: heat map of changes in gene expression over time
(0.5 h, n ? 6; 6 h, n ? 8; 24 h, n ? 7; and 168 h, n ? 6) of
982 differentially expressed probe sets in peripheral blood
mononuclear cells (PBMC) after intravenous endotoxin chal-
lenge. Each row represents a gene probe set and each column
a subject at the respective time point. Change from baseline is
determined by the average difference in the probe set (stan-
dardized and transformed using the symmetric adaptive trans-
form as per METHODS), with increased gene expression de-
picted by red and decreased gene expression depicted by
green. B: heat map of changes in gene expression over time (3
h, n ? 3; 6 h, n ? 4; 24 h, n ? 4; and 168 h, n ? 4) of 224
differentially expressed probe sets in whole blood cells after
intravenous endotoxin challenge. Each row represents a gene
probe set and each column a subject at the respective time
point. Change from baseline is determined by the average
difference in the probe set, as above.
207
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 7

Table 3. Defense response genes altered in peripheral blood
mononuclear cells 6 h after intravenous endotoxin challenge
Probe Set and Gene Name
Fold Change 0–6 h
(95% LCL, UCL)
Pathogen recognition and immune response
40331_at macrophage receptor with collagenous
structure
37220_at Fc fragment of IgG, high affinity la, receptor
for (CD64)
31438_s_at CD163 antigen
32068_at complement component 3a receptor 1
37054_at bactericidal/permeability-increasing protein
37095_r_at formyl peptide receptor-like 1
36753_at leukocyte immunoglobulin-like receptor,
subfamily B (with TM and ITIM domains),
member 4
37148_at leukocyte immunoglobulin-like receptor,
subfamily B (with TM and ITIM domains),
member 3
40310_at toll-like receptor 2
35094_f_at leukocyte immunoglobulin-like receptor,
subfamily A (without TM domain), member 3
37689_s_at Fc fragment of IgG, low affinity IIa,
receptor for (CD32)
36889_at Fc fragment of IgE, high affinity I, receptor
for; gamma polypeptide
36661_s_at CD14 antigen
35036_at complement component 1, q subcomponent,
receptor 1
38533_s_at integrin, alpha M (complement component
receptor 3, alpha; also known as CD11b (p170))
39221_at leukocyte immunoglobulin-like receptor,
subfamily B (with TM and ITIM domains),
member 2
39997_at properdin P factor, complement
34665_g_at Fc fragment of IgG, low-affinity IIb,
receptor for (CD32)
36243_at toll-like receptor 1
37799_at asialoglycoprotein receptor 2
34033_s_at leukocyte immunoglobulin-like receptor,
subfamily A (with TM domain), member 2
37470_at leukocyte-associated Ig-like receptor 1
13.6 (9.3, 20.0)
9.9 (7.2, 13.6)
7.5 (6.1, 9.2)
4.8 (3.5, 6.6)
4.0 (2.5, 6.4)
3.9 (2.8, 5.4)
3.1 (2.4, 4.1)
3.1 (2.3, 4.3)
2.7 (2.2, 3.4)
2.7 (2.3, 3.2)
2.6 (1.7, 3.8)
2.5 (2.1, 3.1)
2.5 (1.9, 3.3)
2.5 (1.6, 3.8)
2.3 (1.7, 3.2)
2.2 (1.6, 3.1)
2.2 (1.6, 3.2)
2.1 (1.5, 2.8)
2.0 (1.5, 2.6)
2.0 (1.4, 2.7)
1.9 (1.4, 2.7)
1.9 (1.6, 2.3)
Chemokine/cytokine receptors
37603_at interleukin 1 receptor antagonist
39994_at chemokine (C-C motif) receptor 1
41140_at interferon gamma receptor 2 (interferon
gamma transducer 1)
36229_at interleukin 17 receptor
41677_at interleukin 15 receptor, alpha
38969_at interleukin 27
39938_g_at chemokine (C-C motif) receptor 2
33227_at interleukin 10 receptor, beta
39424_at tumor necrosis factor receptor superfamily,
member 14 (herpesvirus entry mediator)
35659_at interleukin 10 receptor, alpha
1097_s_at chemokine (C-C motif) receptor 7
1897_at transforming growth factor, beta receptor III
(betaglycan, 300kD)
1404_r_at small inducible cytokine A5 (RANTES)
34077_at G protein-coupled receptor 9
40729_s_at lymphotoxin beta (TNF superfamily,
member 3)
38578_at tumor necrosis factor receptor superfamily,
member 7
1370_at interleukin 7 receptor
31496_g_at small inducible cytokine subfamily C,
member 1 (lymphotactin)
34023_at Fc fragment of IgE, high affinity I, receptor
for; alpha polypeptide
4.7 (3.1, 7.1)
3.0 (2.1, 4.2)
3.0 (2.3, 3.9)
2.5 (1.9, 3.4)
2.5 (1.8, 3.5)
2.4 (1.9, 3.0)
2.2 (1.7, 2.9)
2.1 (1.6, 2.7)
0.7 (0.5, 0.9)
0.6 (0.4, 0.8)
0.5 (0.3, 0.8)
0.4 (0.3, 0.6)
0.4 (0.2, 0.7)
0.4 (0.3, 0.5)
0.4 (0.3, 0.6)
0.3 (0.2, 0.5)
0.3 (0.2, 0.5)
0.3 (0.2, 0.5)
0.1 (0.1, 0.2)
Table 3.—Continued
Probe Set and Gene Name
Fold Change 0–6 h
(95% LCL, UCL)
Growth factors
37494_at colony-stimulating factor 2 receptor, beta,
low affinity (granulocyte-macrophage)
32675_at bone marrow stromal cell antigen 1
36879_at endothelial cell growth factor 1 (platelet-
derived)
39061_at bone marrow stromal cell antigen 2
33665_s_at colony-stimulating factor 2 receptor, alpha,
low affinity (granulocyte-macrophage)
1953_at vascular endothelial growth factor
4.1 (2.0, 8.4)
3.0 (2.4, 3.7)
2.9 (2.1, 4.1)
2.7 (2.1, 3.5)
2.2 (1.5, 3.3)
1.7 (1.3, 2.2)
Microbicidal oxidase and oxidative stress
34666_at superoxide dismutase 2, mitochondrial
38893_at neutrophil cytosolic factor 4 (40kDa)
37975_at cytochrome b-245, beta polypeptide (chronic
granulomatous disease)
824_at glutathione-S-transferase like; glutathione
transferase omega
35807_at cytochrome b-245, alpha polypeptide
39729_at peroxiredoxin 2
9.0 (5.4, 15.0)
3.1 (2.3, 4.1)
2.4 (1.9, 3.2)
1.9 (1.3, 2.8)
1.8 (1.6, 2.1)
0.6 (0.5, 0.7)
Protease and protease inhibitors
31859_at matrix metalloproteinase 9 (gelatinase B,
92kD gelatinase, 92kD type IV collagenase)
36984_f_at haptoglobin-related protein
34761_r_at a disintegrin and metalloproteinase domain
9 (meltrin gamma)
1693_s_at tissue inhibitor of metalloproteinase 1
31891_at chitinase 3-like 2
33305_at serine (or cysteine) proteinase inhibitor, clade
B (ovalbumin), member 1
37021_at cathepsin H
34876_at carboxypeptidase D
40712_at a disintegrin and metalloproteinase domain 8
36781_at serine (or cysteine) proteinase inhibitor, clade
A (alpha-1 antiproteinase), member 1
39581_at cystatin A (stefin A)
44.1 (18.6, 104.6)
5.7 (2.8, 11.8)
4.5 (2.9, 7.0)
4.4 (3.5, 5.6)
3.8 (2.5, 5.5)
3.0 (2.3, 4.0)
2.6 (1.9, 3.4)
2.5 (2.1, 3.1)
2.2 (1.6, 3.1)
1.9 (1.5, 2.5)
1.9 (1.4, 2.7)
Cytotoxin
36766_at ribonuclease, RNase A family, 2 (liver,
eosinophil-derived neurotoxin)
33979_at ribonuclease, RNase A family, 3 (eosinophil
cationic protein)
5.2 (3.5, 7.8)
3.1 (1.9, 5.0)
Arachidonate metabolism
40082_at fatty-acid-coenzyme A ligase, long-chain 2
32775_r_at phospholipid scramblase 1
37099_at arachidonate 5-lipoxygenase-activating protein
39799_at fatty acid-binding protein 5 (psoriasis
associated)
39624_at leukotriene b4 receptor (chemokine receptor-
like 1)
1671_s_at mitogen-activated protein kinase 14
38099_r_at fatty-acid-coenzyme A ligase, long-chain 4
37692_at diazepam-binding inhibitor (GABA receptor
modulator, acyl-coenzyme A-binding protein)
11.5 (7.5, 17.8)
5.2 (3.3, 8.0)
4.5 (3.4, 6.0)
2.2 (1.4, 3.5)
2.0 (1.7, 2.4)
2.0 (1.4, 2.9)
1.8 (1.3, 2.4)
1.8 (1.3, 2.5)
Metal-binding proteins
40456_at upregulated by BCG-CWS
38598_at solute carrier family 11 (proton-coupled
divalent metal ion transporters), member 1
36130_f_at Homo sapiens, similar to RNA helicase-
related protein, clone MGC:9246 IMAGE:3892441
33943_at ferritin, heavy polypeptide 1
Coagulation
35245_at coagulation factor V (proaccelerin, labile
factor)
33803_at thrombomodulin
20.6 (11.8, 36.2)
3.6 (1.6, 8.4)
2.2 (1.7, 2.9)
1.9 (1.3, 2.7)
6.2 (3.7, 10.5)
2.2 (1.5, 3.2)
208
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 8

27-kDa protein 1; HS-binding protein 1, a negative regulator of
HS response].
Transcriptional activator genes responsive to cytokine in-
duction increase in expression including STAT3 (acute-phase
response factor-binding IL-6 response elements), STAT1 (tran-
scription factor that binds IFN-stimulated response elements),
and enhancer of STAT responses (NMI or N-myc). Genes
encoding proteins that bind to regulatory regions involved in
inflammatory responses (especially the IL-1 response element
of IL-6 gene), CCAAT/enhancer-binding protein (CEBP)B and
CEBPD, as well as members of the Fos and JunB family
[which dimerize to regulate AP-1/activating transcription fac-
tor (ATF) transcription sites] are induced. Negative regulators
of transcription appeared as well: BCL6; calreticulin (CALR),
which modulates nuclear hormone receptor activity; BATF, a
regulator of AP-1/ATF transcriptional events; and HSBP1, a
regulator of the HS response.
Table 3.—Continued
Probe Set and Gene Name
Fold Change 0–6 h
(95% LCL, UCL)
S100 calgranulins
34319_at S100 calcium-binding protein P
38879_at S100 calcium-binding protein A12
(calgranulin C)
41471_at S100 calcium-binding protein A9
(calgranulin B)
38138_at S100 calcium-binding protein A11
(calgizzarin)
41096_at S100 calcium-binding protein A8
(calgranulin A)
15.3 (8.6, 27.0)
8.4 (5.9, 12.2)
2.4 (1.9, 3.0)
2.2 (1.8, 2.6)
2.0 (1.6, 2.4)
T- and B cell-associated genes
38006_at CD48 antigen (B-cell membrane protein)
36798_g_at sialophorin (gpL115, leukosialin, CD43)
40667_at CD6 antigen
40688_at linker for activation of T cells
771_s_at CD7 antigen (p41)
40738_at CD2 antigen (p50), sheep red blood cell
receptor
36277_at CD3E antigen, epsilon polypeptide (TiT3
complex)
931_at Epstein-Barr virus-induced gene 2 (lymphocyte-
specific G protein-coupled receptor)
1105_s_at T cell receptor beta locus
32070_at protein tyrosine phosphatase, receptor type,
C-associated protein
41654_at adenosine deaminase
38147_at SH2 domain protein 1A, Duncan’s disease
(lymphoproliferative syndrome)
41468_at T cell receptor gamma locus
1498_at zeta-chain (TCR)-associated protein kinase
(70 kDa)
38319_at CD3D antigen, delta polypeptide (TiT3
complex)
35517_at CD4 antigen (p55)
32794_g_at T cell receptor beta locus
432_s_at T cell receptor alpha locus
1106_s_at T cell receptor alpha locus
37078_at CD3Z antigen, zeta polypeptide (TiT3
complex)
38917_at T cell receptor delta locus
39226_at CD3G antigen, gamma polypeptide (TiT3
complex)
1365_at interleukin 2 receptor, beta
0.7 (0.6, 0.9)
0.6 (0.5, 0.7)
0.5 (0.4, 0.7)
0.5 (0.4, 0.6)
0.5 (0.3, 0.6)
0.4 (0.3, 0.5)
0.4 (0.3, 0.5)
0.4 (0.2, 0.6)
0.4 (0.2, 0.5)
0.3 (0.2, 0.5)
0.3 (0.2, 0.5)
0.3 (0.2, 0.5)
0.3 (0.2, 0.4)
0.3 (0.2, 0.4)
0.3 (0.2, 0.4)
0.3 (0.2, 0.5)
0.3 (0.1, 0.5)
0.3 (0.1, 0.5)
0.3 (0.2, 0.4)
0.3 (0.2, 0.4)
0.3 (0.2, 0.4)
0.2 (0.1, 0.3)
0.1 (0.1, 0.3)
Cytotoxic and NK cells
39239_at CD8 antigen, beta polypeptide 1 (p37)
39119_s_at natural killer cell transcript 4
36887_f_at killer cell immunoglobulin-like receptor,
three domains, long cytoplasmic tail, 1
36280_at granzyme K (serine protease, granzyme 3;
tryptase II)
36777_at DNA segment on chromosome 12 (unique)
2489 expressed sequence
36886_f_at killer cell immunoglobulin-like receptor,
two domains, long cytoplasmic tail, 3
32297_s_at killer cell lectin-like receptor subfamily C,
member 2
32904_at perforin 1 (pore-forming protein)
40699_at CD8 antigen, alpha polypeptide (p32)
40718_at cathepsin W (lymphopain)
32370_at similar to granzyme B (granzyme 2, cytotoxic
T lymphocyte-associated serine esterase 1)
32287_s_at killer cell lectin-like receptor subfamily C,
member 3
35449_at killer cell lectin-like receptor subfamily B,
member 1
40757_at granzyme A (granzyme 1, cytotoxic T
lymphocyte-associated serine esterase 3)
0.5 (0.4, 0.7)
0.4 (0.2, 0.6)
0.3 (0.2, 0.8)
0.3 (0.2, 0.5)
0.3 (0.2, 0.5)
0.3 (0.2, 0.6)
0.3 (0.2, 0.6)
0.3 (0.2, 0.5)
0.3 (0.2, 0.5)
0.3 (0.2, 0.3)
0.2 (0.1, 0.4)
0.2 (0.1, 0.4)
0.2 (0.1, 0.3)
0.2 (0.1, 0.3)
Table 3.—Continued
Probe Set and Gene Name
Fold Change 0–6 h
(95% LCL, UCL)
37145_at granulysin
32264_at granzyme M (lymphocyte met-ase 1)
0.1, (0.1, 0.3)
0.1 (0.0, 0.2)
MHC and APC
32035_at major histocompatibility complex, class II,
DR beta 4
36270_at CD86 antigen (CD28 antigen ligand 2, B7-2
antigen)
36878_f_at major histocompatibility complex, class II,
DQ beta 1
38833_at major histocompatibility complex, class II,
DP alpha 1
38096_f_at major histocompatibility complex, class II,
DP beta 1
41609_at major histocompatibility complex, class II,
DM beta
36155_at KIAA0275 gene product
0.7 (0.1, 1.2)
0.6 (0.4, 0.7)
0.4 (0.3, 0.7)
0.4 (0.3, 0.5)
0.4 (0.3, 0.5)
0.3 (0.3, 0.4)
0.3 (0.2, 0.5)
Apoptosis
33727_r_at tumor necrosis factor receptor superfamily,
member 6b, decoy
2002_s_at BCL2-related protein A1
1497_at lymphotoxin beta receptor (TNFR superfamily,
member 3)
33412_at lectin, galactoside binding, soluble, 1
(galectin 1)
1563_s_at tumor necrosis factor receptor superfamily,
member 1A
32725_at BH3-interacting domain death agonist
2066_at BCL2-associated X protein
31536_at reticulon 4
37643_at tumor necrosis factor receptor superfamily,
member 6
41189_at tumor necrosis factor receptor superfamily,
member 12
31491_s_at caspase 8, apoptosis-related cysteine
protease
849_g_at TNF receptor-associated factor 1
35238_at TNF receptor-associated factor 5
37127_at death effector filament-forming Ced-4-like
apoptosis protein
1847_s_at B cell CLL/lymphoma 2
32967_at regulator of Fas-induced apoptosis
6.0 (2.9, 12.7)
4.8 (3.0, 7.6)
3.7 (2.0, 6.9)
2.3 (1.8, 2.9)
1.9 (1.6, 2.3)
1.9 (1.4, 2.5)
1.8 (1.5, 2.2)
1.8 (1.5, 2.1)
1.7 (1.3, 2.3)
0.6 (0.5, 0.8)
0.6 (0.4, 0.8)
0.6 (0.4, 0.7)
0.5 (0.4, 0.6)
0.5 (0.3, 0.8)
0.5 (0.3, 0.7)
0.4 (0.3, 0.5)
LCL, lower confidence limit; UCL, upper confidence limit; NK cells, natural
killer cells; MHC, major histocompatibility complex; APC, antigen presenting
cell.
209
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 9

Table 4. Atypical acute-phase genes differentially regulated after intravenous endotoxin challenge
Association of Gene Products with Disease
Function or Disorder
Fold
Change
LCL
95%
UCL
95%Probe set Gene SymbolTitle
Induced
35245_at F5 coagulation factor V (proaccelerin, labile
factor)
CD63 antigen (melanoma 1 antigen)
c-mer proto-oncogene tyrosine kinase
activin A receptor type II-like 1
Janus kinase 3 (a protein tyrosine kinase,
leukocyte)
neutrophil cytosolic factor 1 (47kD)
huntingtin interacting protein 1
hemorrhagic diathesis 5.63.39.2
37003_at
1786_at
40594_r_at
1547_at
CD63
MERTK
ACVRL1
JAK3
Hermansky-Pudlak syndrome
retinitis pigmentosa
Rendu-Osler-Weber syndrome 2
autosomal SCID (severe combined
immunodeficiency disease).
chronic granulomatous disease.
cytoskeleton disease, Huntingtons
disease
cyclic neutropenia
sialidosis
X-linked chronic granulomatous
disease
altered expression cystic fibrosis
4.0
3.2
2.8
2.8
2.9
2.1
1.0
1.3
5.5
4.8
7.6
6.1
40159_r_at
41061_at
NCF1
HIP1
2.8
2.6
1.7
1.8
4.6
3.9
37096_at
39075_at
37975_at
ELA2
NEU1
CYBB
elastase 2, neutrophil
sialidase 1 (lysosomal sialidase)
cytochrome b-245, beta polypeptide
2.6
2.4
2.2
1.1
1.4
1.7
5.9
4.3
2.8
41471_at S100A9S100 calcium binding protein A9
(calgranulin B)
acyl-Coenzyme A oxidase 1, palmitoyl
ATPase, Ca?? transporting, cardiac
muscle, slow twitch 2
retinoblastoma 1 (including osteosarcoma)
vitelliform macular dystrophy
retinitis pigmentosa 2 (X-linked recessive)
phosphorylase, glycogen; liver
2.2 1.72.7
40459_at
39791_at
ACOX1
ATP2A2
pseudoneonatal adrenoleukodystrophy
Darier-White disease, keratosis
follicularis
embryonic malignant neoplasm
bestrophin, macular dystrophy
retinitis pigmentosa
Hers disease, glycogen storage disease
type VI
glycolipid transport, Tay-Sachs disease
Ehlers-Danlos syndrome type VI
2.1
2.1
1.4
1.6
3.2
2.7
2044_s_at
38601_at
39964_at
37215_at
RB1
VMD2
RP2
PYGL
2.0
2.0
2.0
2.0
1.3
1.4
1.4
1.6
3.1
2.9
2.9
2.5
35820_at
36184_at
GM2A
PLOD
GM2 ganglioside activator protein
procollagen-lysine, 2-oxoglutarate 5-
dioxygenase
transducin (beta)-like 2
2.0
1.9
1.4
1.4
2.8
2.6
36090_atTBL2 intracellular signaling, deleted in
William-Beuren Syndrome
mitochondrial enzyme, autosomal
recessive eye disease, gyrate atrophy
Fabray disease and X-linked
agammaglobulinemia
orthostatic intolerance
Clouston hidrotic ectodermal dysplasia
and Kabuki syndrome
fatal infantile
cardioencephalomyopathy,
hypertrophic cardiomyopathy, lactic
acidosis, gliosis
protein interacts with autoantigens of
Sjogrens and systemic lupus
Autosomal recessive chronic
granulomatous disease
glycogen storage disease IV
(Andersen’s disease)
hereditary multiple exostoses
cystinosis
mental retardation or Alport syndrome
1.91.4 2.4
36636_at OATornithine aminotransferase (gyrate
atrophy)
heterogeneous nuclear ribonucleoprotein
H2 (Hl)
solute carrier family 6 member 2
tubulin, alpha 2
1.91.52.3
41131_f_atHNRPH2
1.8 1.5 2.3
40402_at
38350_f_at
SLC6A2
TUBA2
1.7
1.7
1.2
1.2
2.6
2.4
40639_atSCO2SCO cytochrome oxidase deficient
homolog 2 (yeast)
1.7 0.93.2
37126_atSSA1 Sjogren syndrome antigen A1 (52kD) 1.71.51.9
35807_at CYBAcytochrome b-245, alpha polypeptide1.61.51.8
32643_atGBE1glucan (1,4-alpha-), branching enzyme 11.61.42.0
222_at
36566_at
38099_r_at
EXT1
CTN5
FACL4
exostoses (multiple) 1
cystinosis, nephropathic
fatty-acid-Coenzyme A ligase, long-chain
4
Nijmegen breakage syndrome 1 (nibrin)
1.6
1.6
1.6
1.2
1.2
1.2
2.2
2.2
2.2
35153_atNBS1mental retardation, microcephaly,
growth retardation,
immunodeficiency, and cancer
immunodeficiency associated with
recurrent infectious
1.6 1.22.0
38378_atCD53CD53 antigen 1.51.41.8
Repressed
38789_at
31330_at
TKT
RPS19
transketolase
ribosomal protein S19
Wernicke-Korsakoff syndrome
Diamond-Blackfan anemia
(erythroblastopenia)
mental retardation, Rett syndrome
mental retardation
0.7
0.6
0.5
0.5
0.9
0.7
34355_at
37543_at
MECP2
ARHGEF6
methyl CpG binding protein 2
Rac/Cdc42 guanine nucleotide exchange
factor (GEF) 6
small nuclear ribonucleoprotein
polypeptide N
mannose phosphate isomerase
0.5
0.5
0.4
0.5
0.7
0.6
34842_atSNRPNAngelman syndrome or Prader-Willi
syndrome
carbohydrate deficient glycoprotein
synthesis, type 1b
0.40.30.6
36673_at MPI0.40.30.6
210
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 10

Repression of Genes After Endotoxin Administration
Signals initiated by the induction of innate immunity (i.e.,
cytokine, chemokine, and co-stimulatory molecules) control
the activation of adaptive immune responses (Table 3). Acti-
vated antigen-presenting cells process proteins from microor-
ganisms into antigenic peptides that are complexed with MHC
class II molecules on the cell surface and, in conjunction with
co-stimulatory molecules (CD80, CD86), activate T cells.
Within hours of the sterile inflammation induced by endotoxin,
we observed suppression of genes associated with antigen
presenting cell function (CD86, MHC complex class II anti-
gens) and T and B lymphocyte genes (adenosine deaminase; T
cell receptor complex components; CD2-, CD3-, and CD4-
related genes; IL-2 receptor). Genes associated with T and B
cell receptor activation (TNFRSF7) and one of its binding
proteins [CD27-binding (siva) protein] as well as CD160,
which activates NK, and cytolytic T cells are repressed.
Genes associated with NK cells were likewise suppressed
(killer cell lectin-like receptors, or KLRC), as were killer
inhibitory receptors (KIR2DL3, KIR3DL1). The latter bind
human leukocyte antigen (HLA) class I molecules and are
associated with inhibitory cell signals. Genes associated with
cell products from cytolytic T cells and NK cells that have a
direct lytic potential for target cells were repressed (granulysin;
perforin; granzyme A, M, and K; cathepsin).
Cytokines, chemokines, and chemokine receptors that regu-
late lymphocyte activation (lymphotoxin LTB) and trafficking
(CCL5-RANTES, XCL1 lymphotactin) are downregulated, as
are G protein-coupled chemokine receptors (CCR7 and
CXCR3). Suppression of multiple genes associated with pro-
tein synthesis (ribosomal genes), translation, and processing
was observed.
Forty-eight genes whose absence or mutation has been
associated with overt immunodeficiency (i.e., JAK3, NCF1,
CYBA, LRBA), metabolic defects (i.e., CTNS, PYGL,
GM2A), neurological syndromes (i.e., TBL2, HIP1, FACL4),
tumorgenesis (i.e., RB1, NBS1, CD63), and eye diseases (i.e.,
VMD2, RP2) were differentially regulated by endotoxin. Many
of these genes have not typically been associated with the
acute-phase response or innate immunity (Table 4).
Gene Expression in Whole Blood Samples
To assess changes in a complementary tissue, we measured
gene expression in whole blood from four subjects (Fig. 2B and
Supplemental Table S3A). Whole blood gene expression was
altered at 3 h (40 up- and 9 downregulated genes), 6 h (100 up-
and 92 downregulated genes), and 24 h (1 upregulated gene).
No genes in whole blood were differentially regulated at 168 h.
At 6 h, we measured simultaneous changes in gene expression
in the PBMC of the same four subjects; 134 genes were
induced and 129 genes were repressed compared with baseline.
Twenty-nine induced and 32 repressed genes were common
between the PBMC and whole blood samples. GO categories
that were significantly (P ? 0.01) represented among these
genes are depicted by GO-MAPs found in Supplemental Table
S3, B (induced genes) and C (repressed genes).
The defense response was an overrepresented gene category
that included genes from the afferent arm of innate immunity
(peptidoglycan recognition protein, TLR5, CD14, C3aR1,
LILRA3),intracellular signaling
MAP4K4, FGR, JUNB), transcription factors (NFkB2, BATF,
ETV6), cell mobility (VASP, LIMK2, MARCKS, aquaporin
9), and cytokine and cytokine receptors (IL-1?, IL-1RAP,
IL-1RN, IL-1RII, IL-4R, IL-18R, IL-18RAP) (Supplemental
Table S3B).
Downregulated defense response included T cell- and B
cell-associated genes [CD2 antigen (p50); CD3D antigen; T
cell receptor-?, -?, and -?; CD79A; CD79B], cytolytic and NK
cell-associated genes (perforin 1, granulysin, granzyme M),
MHC molecules (MHC II DP-?1 and -?1, MHC II DQ-?1),
and cytokine receptors (IL-2R?, IL-7R) as well as genes for
multiple ribosomal proteins (Supplemental Table S3C).
Thus similar biological themes emerge from analysis of
whole blood gene expression compared with mononuclear
cells: increased gene expression associated with the defense
response and response to pathogens, and decreased expression
proteins (MAPK14,
Table 4.—Continued
Association of Gene Products with Disease
Function or Disorder
Fold
Change
LCL
95%
UCL
95%Probe set Gene SymbolTitle
41814_at FUCA1 fucosidase, alpha-L- 1, tissueautosomal recessive lysosomal storage
disease
ataxia telangectasia
defective in Duchenne muscular
dystrophy
Ehler-Danlos syndrome, osteogenesis
imperfecta
Chediak-Higashi syndrome
0.40.3 0.6
2000_at
41866_s_at
ATM
DTNB
ataxia telangiectasia mutated
dystrobrevin, beta
0.4
0.4
0.3
0.2
0.6
0.7
38063_at PBXIP1hematopoietic PBX-interacting protein 0.40.30.5
35371_atLRBAvesicle trafficking, beach and anchor
containing
junction plakoglobin
0.40.30.5
2047_s_at JUParrhythmogenic right ventricular
cardiomyopathy, palmoplantar
keratoderma, woolly hair
severe combined immunodeficiency
mutations in Parkinson disease,
chronic obstructive pulmonary
disease
a single-nucleotide polymorphism is
associated with susceptibility to
myocardial infarction.
0.30.20.7
1370_at
33825_at
IL7R
SERPINA3
interleukin 7 receptor
serine (or cysteine) proteinase inhibitor,
clade A, member 3
0.3
0.2
0.1
0.1
0.5
0.5
37456_at LGALS2 lectin, galactoside-binding, soluble, 2
(galectin 2) 3
0.1 0.0 0.2
211
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 11

of genes associated with lymphocytes and ribosomal proteins
(Supplemental Table S4).
Quantitative PCR and Array Expression
Confirmatory assays of relative gene expression across a
range of array expression were performed on 12 genes using
real-time quantitative PCR (TaqMan). Results are represented
in fold change, comparing 6 with 0 h. TaqMan fold changes
were comparable with the array results (Fig. 3).
DISCUSSION
To model gene profiles in the early phases of a systemic
infection, we administered endotoxin to normal volunteers and
measured serial changes in gene expression in PBMC and
whole blood. The greatest changes occurred by 6 h and re-
solved by 24 h. Exposure to a single microbial component
resulted in a rich variety of changes in gene expression includ-
ing the induction of genes associated with pattern recognition
molecules, signal transduction, transcription factors, cell mo-
bility, cell proliferation, and microbial killing, the downregu-
lation of lymphocyte-associated genes, and expression of genes
not previously associated with endotoxemia or acute inflam-
mation. The endotoxin phenotype did not persist in the blood
transcriptome at 24 h. This broad and rapid on-off response of
gene expression is in stark contrast to the sustained inflamma-
tory phenotype that occurs during clinical sepsis, due in part to
continued exposure to microbial components with recruitment
of pathways that promote a sustained inflammatory response
(3, 25). Several different counterregulatory mechanisms may
have contributed to the extinction of the endotoxin phenotype:
anti-inflammatory cytokines (i.e., IL-1 receptor antagonist,
IL-10), inflammatory mediator clearance, removal of circulat-
ing inflammatory cells by adherence to endothelium or by
apoptosis, and marrow replenishment of cells to the circulation.
Human immune cell responses to pathogens and their com-
ponents have a shared core pattern of gene expression as well
as pathogen-specific responses (26, 38). Monocyte-derived
macrophages activate genes encoding receptors, signal trans-
duction molecules, and transcription factors that prime the
macrophage for subsequent environmental interactions (38).
Gene profiles induced by endotoxin stimulation of monocyte-
derived dendritic cells mimic almost the entire core gene
expression induced by intact bacteria in vitro (26). While
transcript levels of genes associated with phagocytosis and
pathogen recognition decline immediately after contact with
pathogens, a wide variety of genes associated with immunity
are activated (26). Gene levels of cytokines, chemokines and
their receptors, and cytoskeleton, signaling, and transcription
factors are increased. Antigen processing and presentation
genes as well as genes involved in reactive oxygen species are
induced in a sustained fashion (26). In contrast to these studies
of in vitro monocyte-derived cells, our expression profiles of
PBMC and whole blood in vivo show a strong upregulation of
genes associated with pathogen recognition and phagocytosis
at 6 h.
Other investigators have evaluated gene expression changes
in PBMC in vitro after exposure to endotoxin or killed bacteria
using amplified polyA RNA and a cDNA microarray format
(7). A stereotypic program of gene expression was found with
the preponderance of induced genes associated with cell-cell
signaling pathways and proinflammatory mediators and re-
pressed genes that included chemokine and chemokine recep-
tors, pathogen recognition and adhesion molecules, compo-
nents of the respiratory burst, and genes encoding MHC class
II molecules (7). Only a modest overlap was found between
our 439 induced genes at 6 h and those described by Boldrick
et al. (7) in PBMC stimulated with endotoxin; 35 (7.8%) of our
induced genes were found in their gene database. Eleven genes
were concordant whereas 24 were discordant with the direction
of change. Of our 428 repressed genes observed at 6 h after
endotoxin, 50 (12%) were found in their database: 30 were
concordant and 20 were discordant with our results. Our gene
list differs from these in vitro observations with an enhanced
role for genes associated with pathogen recognition, chemo-
kines and their receptors, adhesion molecules, and respiratory
burst but is similar regarding the suppression of MHC class II
genes.
The lack of similarity of our observations of gene expression
in PBMC after endotoxin challenge with in vitro data may be
due to culture conditions and different array targets (i.e., arrays
enriched for detection of lymphocyte-associated genes) (7).
Gene expression profiles obtained from in vitro experiments
provide important information regarding gene expression po-
tential, yet several factors must be considered when extrapo-
lating these results to clinical states. Cell isolation and culture
conditions, including in vitro differentiation (i.e., monocyte-
derived macrophages or dendritic cells), may affect gene ex-
pression profiles (14, 30). Cultured cells stimulated with en-
dotoxin are further altered by the accumulation of secreted
mediators. The lack of primary and secondary mediator clear-
Fig. 3. Real-time PCR (RT-PCR) was used to validate the microarray results
for PBMC data sets (TaqMan PCR detection, Applied Biosystems). Probes and
primers for 12 target sequences were designed using Primer Express computer
software (Applied Biosystems). Data are presented as median values [?95%
confidence limit (CL)]; n ? 4. CD8A, CD8 antigen, ?-polypeptide (p32);
CD3G, CD3G antigen, ?-polypeptide (TiT3 complex); SH2D1A, SH2 domain
protein 1A; TRB, T cell receptor-? locus; IL7R, interleukin (IL)-7 receptor;
LAT, linker for activation of T cells; CSFR2, colony-stimulating factor 2
receptor-?, low affinity; FAS, tumor necrosis factor receptor superfamily,
member 6; SOD2, superoxide dismutase 2, mitochondrial; ADM, ad-
renomedullin; S100A12, S100 calcium-binding protein A12; MMP9, matrix
metalloproteinase 9.
212
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 12

ance limits the ability to assess physiological levels of inflam-
matory molecules on gene expression. Furthermore, expression
profiling of isolated cells precludes an assessment of cell
interactions on differential gene regulation. Thus fundamen-
tally different information is obtained from assessment of gene
expression in vivo.
Mononuclear cells undergo changes in number and propor-
tion after endotoxin challenge, and this will affect the relative
contribution of RNA associated with a specific cell type (i.e., T
lymphocyte) in the array results. Activated T cells contain
almost twice as much total RNA as resting cells (49), and
analyses based on the proportion of cells present in a mixed
cell sample may not account for differences in RNA content
per cell. In our study, the percentage of T lymphocytes re-
mained constant within the PBMC preparation (Fig. 1). When
a fixed proportion of blood cells (whole blood) are stimulated
in vitro with endotoxin, genes for ribosomal proteins, cytotoxic
T lymphocyte factors, and T cell receptor and nuclear activa-
tion factors are downregulated, similar to our in vivo observa-
tions (22). A functional consequence of ribosomal gene down-
regulation in vitro and in vivo is suggested by a decrease in T
lymphocyte protein synthesis (?58%) immediately after endo-
toxin challenge in humans (27).
Animal and human studies of systemic endotoxin challenge
further support our observations. Whole blood arrays of rats
challenged with endotoxin show that ribosomal and MHC class
II genes are repressed as observed in the current study (20).
With the use of a cDNA array, qualitative changes in 23
downregulated (i.e., ribosomal genes and HLA antigens) and
31 upregulated genes (i.e., transcription factors, cytokines,
CD14, and mitochondrial proteins) were described in humans
challenged with either 2 or 3 ng/kg endotoxin (40). The
relationship of mRNA and protein expression for cytokines,
cytokine receptors, and adhesion molecules was variable, sug-
gesting either non-PBMC sources of protein or the effects of
posttranscriptional regulatory events (40).
Recently, other investigators (8) have studied the effects of
endotoxin (2 ng/kg) in four healthy subjects and, using a
higher-density oligonucleotide array, described differential
regulation of 3,714 genes in whole blood leukocytes. Their
analysis revealed dysregulation of leukocyte bioenergetics and
modulation of translational machinery. Genes for cytokines
and chemokines and their receptors as well as members of the
NF-?/relA family of transcription factors were activated within
the first 2–4 h (8). These data complement our observations by
providing data from whole blood leukocytes (buffy coat) with
similar differentially regulated genes and biological themes.
We compared our 6-h mononuclear cell data (HU95Av2
microarray, Affymetrix) with the 6-h whole blood data
(HU133A/B, Affymetrix) from Calvano et al. (8). Using a
?50% increased or decreased relative change from baseline,
we evaluated probe sets in common and different between the
two studies (Supplemental Table S5). We found 162 induced
and 299 repressed probe sets that were common between the
two studies and noted 264 upregulated and 143 downregulated
probe sets unique to PBMC and distinct from the 281 (upregu-
lated) and 856 (downregulated) probe sets discovered by Cal-
vano et al. in whole blood (Supplemental Table S5). The
unique PBMC probe sets included genes associated with heat
shock proteins and chemokine and cytokine receptors (all
induced) and an enrichment of T lymphocyte-associated genes
(repressed). These data demonstrate that, while a common set
of genes are expressed in blood leukocytes after endotoxin
challenge, unique gene expression profiles emerge when en-
riching the RNA pool with specific cell types such as PBMC.
The repression of genes associated with lymphocytes in
PBMC and whole blood preparations is consistent with previ-
ous observations of a state of immunosuppression that occurs
after acute inflammation (3, 25, 36). We found that, while an
early marker of lymphocyte activation (CD69 surface marker
expression) was increased on lymphocytes after endotoxin
challenge, a broad category of genes associated with T and B
cell surface receptors, NK cell-related cytolytic granules, and
MHC antigens were downregulated. Th1 cytokine (IL-2 and
IFN-?) blood levels did not increase. IL-10 levels increased in
blood, whereas other Th2 cytokines (IL-4 and IL-5) were
unchanged. Mice stimulated with endotoxin activate T cells, as
reflected by increased CD69 and CD25 expression, but have a
decreased capacity to produce Th1 cytokines (9). Whole blood
obtained from volunteers after intravenous endotoxin challenge
respond to T cell stimuli with reduced IFN-? and IL-2 produc-
tion, and this tolerant state was due in part to serum factors
(29). Similarly, mononuclear cells from patients with sepsis or
traumatic injury or in the postoperative state have decreased
responsiveness to secondary stimuli (i.e., endotoxin, anti-CD3/
CD28) with impaired Th1 cytokine secretion and T cell pro-
liferative responses and decreased expression of HLA-DR
molecules (2, 13, 15, 18, 24). This tolerance phenomenon has
been postulated to be an adaptive response to limit tissue
damage (10). However, tolerance is not characterized by a
global hyporesponsiveness to all bacterial components (2). The
latter case is consistent with our observation of increased
expression of genes associated with pathogen recognition mol-
ecules.
We analyzed whole blood cells with the PAXgene blood
collection system, which has the advantage of rapid stabiliza-
tion of nucleic acids on collection. This ease of sample acqui-
sition facilitates its use in clinical studies. However, this
method has limitations because of an abundant globin and
reticulocyte message that contributes to increased signal noise
and decreased sensitivity compared with gene expression pro-
files of blood cells isolated by other methods (12, 19, 21).
Despite these limitations, we show that similar biological
themes of whole blood compared with PBMC emerge from
analysis of the activated cells at 6 h.
Thus the interrogation of the transcriptome associated with
endotoxin-induced inflammation integrates a broad variety of
biological themes that collectively reflect the activation of
innate immunity. We conclude that, while some of the ob-
served changes in gene expression on endotoxin administration
are due to gene regulation at a single cell level (i.e., changes in
the transcriptome), others may be caused by changes in the
proportion of each blood cell type (e.g., different subtypes of
mononuclear cells) and are not due to gene regulation. Further
experiments are needed to determine which of the differentially
expressed genes are regulated at the mRNA level. Neverthe-
less, it is likely that a significant fraction of the observed
changes are due to gene regulation, and that the group of
regulated genes reveals a broad variety of biological themes
that reflect the activation of innate immunity. The pathway
redundancy and parallelism of the innate immunity support the
usefulness of broadly acting anti-inflammatory agents during
213
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 13

severe infections (35). These observations provide a blueprint
of expected changes as well as new pathways and molecules
that are engaged during the early response to this common
bacterial component.
GRANTS
This work was supported by NIH intramural funds.
REFERENCES
1. [No author listed.] American College of Chest Physicians/Society of
Critical Care Medicine Consensus Conference: definitions for sepsis and
organ failure and guidelines for the use of innovative therapies in sepsis.
Crit Care Med 20: 864–874, 1992.
2. Adib-Conquy M, Moine P, Asehnoune K, Edouard A, Espevik T,
Miyake K, Werts C, and Cavaillon JM. Toll-like receptor-mediated
tumor necrosis factor and interleukin-10 production differ during systemic
inflammation. Am J Respir Crit Care Med 168: 158–164, 2003.
3. Annane D, Bellissant E, and Cavaillon JM. Septic shock. Lancet 365:
63–78, 2005.
4. Bernard GR, Vincent JL, Laterre PF, LaRosa SP, Dhainaut JF,
Lopez-Rodriguez A, Steingrub JS, Garber GE, Helterbrand JD, Ely
EW, and Fisher CJ Jr. Efficacy and safety of recombinant human
activated protein C for severe sepsis. N Engl J Med 344: 699–709, 2001.
5. Beutler B. Innate immunity: an overview. Mol Immunol 40: 845–859,
2004.
6. Beutler B and Rietschel ET. Innate immune sensing and its roots: the
story of endotoxin. Nat Rev Immunol 3: 169–176, 2003.
7. Boldrick JC, Alizadeh AA, Diehn M, Dudoit S, Liu CL, Belcher CE,
Botstein D, Staudt LM, Brown PO, and Relman DA. Stereotyped and
specific gene expression programs in human innate immune responses to
bacteria. Proc Natl Acad Sci USA 99: 972–977, 2002.
8. Calvano SE, Xiao W, Richards DR, Felciano RM, Baker HV, Cho RJ,
Chen RO, Brownstein BH, Cobb JP, Tschoeke SK, Miller-Graziano
C, Moldawer LL, Mindrinos MN, Davis RW, Tompkins RG, and
Lowry SF. A network-based analysis of systemic inflammation in hu-
mans. Nature 437: 1032–1037, 2005.
9. Castro A, Bemer V, Nobrega A, Coutinho A, and Truffa-Bachi P.
Administration to mouse of endotoxin from gram-negative bacteria leads
to activation and apoptosis of T lymphocytes. Eur J Immunol 28: 488–
495, 1998.
10. Cavaillon JM, Adrie C, Fitting C, and Adib-Conquy M. Endotoxin
tolerance: is there a clinical relevance? J Endotoxin Res 9: 101–107, 2003.
11. Cobb JP, Mindrinos MN, Miller-Graziano C, Calvano SE, Baker HV,
Xiao W, Laudanski K, Brownstein BH, Elson CM, Hayden DL,
Herndon DN, Lowry SF, Maier RV, Schoenfeld DA, Moldawer LL,
Davis RW, Tompkins RG, Bankey P, Billiar T, Camp D, Chaudry I,
Freeman B, Gamelli R, Gibran N, Harbrecht B, Heagy W, Heimbach
D, Horton J, Hunt J, Lederer J, Mannick J, McKinley B, Minei J,
Moore E, Moore F, Munford R, Nathens A, O’Keefe G, Purdue G,
Rahme L, Remick D, Sailors M, Shapiro M, Silver G, Smith R,
Stephanopoulos G, Stormo G, Toner M, Warren S, West M, Wolfe S,
and Young V. Application of genome-wide expression analysis to human
health and disease. Proc Natl Acad Sci USA 102: 4801–4806, 2005.
12. Debey S, Schoenbeck U, Hellmich M, Gathof BS, Pillai R, Zander T,
and Schultze JL. Comparison of different isolation techniques prior gene
expression profiling of blood derived cells: impact on physiological
responses, on overall expression and the role of different cell types.
Pharmacogenomics J 4: 193–207, 2004.
13. Decker D, Schondorf M, Bidlingmaier F, Hirner A, and von Ruecker
AA. Surgical stress induces a shift in the type-1/type-2 T-helper cell
balance, suggesting down-regulation of cell-mediated and up-regulation of
antibody-mediated immunity commensurate to the trauma. Surgery 119:
316–325, 1996.
14. Dietz AB, Bulur PA, Knutson GJ, Matasic R, and Vuk-Pavlovic S.
Maturation of human monocyte-derived dendritic cells studied by microar-
ray hybridization. Biochem Biophys Res Commun 275: 731–738, 2000.
15. Docke WD, Randow F, Syrbe U, Krausch D, Asadullah K, Reinke P,
Volk HD, and Kox W. Monocyte deactivation in septic patients: resto-
ration by IFN-gamma treatment. Nat Med 3: 678–681, 1997.
16. Durbin BP, Hardin JS, Hawkins DM, and Rocke DM. A variance-
stabilizing transformation for gene-expression microarray data. Bioinfor-
matics 18, Suppl 1: S105–S110, 2002.
17. Eichacker PQ, Parent C, Kalil A, Esposito C, Cui X, Banks SM,
Gerstenberger EP, Fitz Y, Danner RL, and Natanson C. Risk and the
efficacy of antiinflammatory agents: retrospective and confirmatory stud-
ies of sepsis. Am J Respir Crit Care Med 166: 1197–1205, 2002.
18. Ertel W, Kremer JP, Kenney J, Steckholzer U, Jarrar D, Trentz O,
and Schildberg FW. Downregulation of proinflammatory cytokine re-
lease in whole blood from septic patients. Blood 85: 1341–1347, 1995.
19. Fan H and Hegde PS. The transcriptome in blood: challenges and
solutions for robust expression profiling. Curr Mol Med 5: 3–10, 2005.
20. Fannin RD, Auman JT, Bruno ME, Sieber SO, Ward SM, Tucker CJ,
Merrick BA, and Paules RS. Differential gene expression profiling in
whole blood during acute systemic inflammation in lipopolysaccharide-
treated rats. Physiol Genomics 21: 92–104, 2005.
21. Feezor RJ, Baker HV, Mindrinos M, Hayden D, Tannahill CL,
Brownstein BH, Fay A, MacMillan S, Laramie J, Xiao W, Moldawer
LL, Cobb JP, Laudanski K, Miller-Graziano CL, Maier RV, Schoen-
feld D, Davis RW, and Tompkins RG. Whole blood and leukocyte RNA
isolation for gene expression analyses. Physiol Genomics 19: 247–254,
2004.
22. Feezor RJ, Oberholzer C, Baker HV, Novick D, Rubinstein M,
Moldawer LL, Pribble J, Souza S, Dinarello CA, Ertel W, and
Oberholzer A. Molecular characterization of the acute inflammatory
response to infections with gram-negative versus gram-positive bacteria.
Infect Immun 71: 5803–5813, 2003.
23. Fong YM, Marano MA, Moldawer LL, Wei H, Calvano SE, Kenney
JS, Allison AC, Cerami A, Shires GT, and Lowry SF. The acute
splanchnic and peripheral tissue metabolic response to endotoxin in
humans. J Clin Invest 85: 1896–1904, 1990.
24. Hensler T, Hecker H, Heeg K, Heidecke CD, Bartels H, Barthlen W,
Wagner H, Siewert JR, and Holzmann B. Distinct mechanisms of
immunosuppression as a consequence of major surgery. Infect Immun 65:
2283–2291, 1997.
25. Hotchkiss RS and Karl IE. The pathophysiology and treatment of sepsis.
N Engl J Med 348: 138–150, 2003.
26. Huang Q, Liu D, Majewski P, Schulte LC, Korn JM, Young RA,
Lander ES, and Hacohen N. The plasticity of dendritic cell responses to
pathogens and their components. Science 294: 870–875, 2001.
27. Januszkiewicz A, Lore K, Essen P, Andersson B, McNurlan MA,
Garlick PJ, Ringden O, Andersson J, and Wernerman J. Response of
in vivo protein synthesis in T lymphocytes and leucocytes to an endotoxin
challenge in healthy volunteers. Clin Exp Immunol 130: 263–270, 2002.
28. Jison ML, Munson PJ, Barb JJ, Suffredini AF, Talwar S, Logun C,
Raghavachari N, Beigel JH, Shelhamer JH, Danner RL, and Gladwin
MT. Blood mononuclear cell gene expression profiles characterize the
oxidant, hemolytic, and inflammatory stress of sickle cell disease. Blood
104: 270–280, 2004.
29. Lauw FN, ten Hove T, Dekkers PE, de Jonge E, van Deventer SJ, and
van Der Poll T. Reduced Th1, but not Th2, cytokine production by
lymphocytes after in vivo exposure of healthy subjects to endotoxin. Infect
Immun 68: 1014–1018, 2000.
30. Le Naour F, Hohenkirk L, Grolleau A, Misek DE, Lescure P, Geiger
JD, Hanash S, and Beretta L. Profiling changes in gene expression
during differentiation and maturation of monocyte-derived dendritic cells
using both oligonucleotide microarrays and proteomics. J Biol Chem 276:
17920–17931, 2001.
31. Malech HL. Phagocytic cells: egress from marrow and diapedesis. In:
Inflammation: Basic Principles and Clinical Correlates, edited by Gallin
JI, Goldstein IM, and Snyderman R. New York: Raven, 1988, p. 297–308.
32. Martin GS, Mannino DM, Eaton S, and Moss M. The epidemiology of
sepsis in the United States from 1979 through 2000. N Engl J Med 348:
1546–1554, 2003.
33. Medzhitov R and Janeway C Jr. Innate immunity. N Engl J Med 343:
338–344, 2000.
34. Meisner M, Muller V, Khakpour Z, Toegel E, and Redl H. Induction
of procalcitonin and proinflammatory cytokines in an anhepatic baboon
endotoxin shock model. Shock 19: 187–190, 2003.
35. Minneci PC, Deans KJ, Banks SM, Eichacker PQ, and Natanson C.
Meta-analysis: the effect of steroids on survival and shock during sepsis
depends on the dose. Ann Intern Med 141: 47–56, 2004.
36. Munford RS and Pugin J. Normal responses to injury prevent systemic
inflammation and can be immunosuppressive. Am J Respir Crit Care Med
163: 316–321, 2001.
37. Nathan C. Points of control in inflammation. Nature 420: 846–852, 2002.
214
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from

Page 14

38. Nau GJ, Richmond JF, Schlesinger A, Jennings EG, Lander ES, and
Young RA. Human macrophage activation programs induced by bacterial
pathogens. Proc Natl Acad Sci USA 99: 1503–1508, 2002.
39. Pajkrt D, Manten A, van der Poll T, Tiel-van Buul MM, Jansen J,
Wouter ten Cate J, and van Deventer SJ. Modulation of cytokine
release and neutrophil function by granulocyte colony-stimulating factor
during endotoxemia in humans. Blood 90: 1415–1424, 1997.
40. Prabhakar U, Conway TM, Murdock P, Mooney JL, Clark S, Hedge
P, Bond BC, Jazwinska EC, Barnes MR, Tobin F, Damian-Iordachi V,
Greller L, Hurle M, Stubbs AP, Li Z, Valoret EI, Erickson-Miller C,
Cass L, Levitt B, Davis HM, Jorkasky DK, and Williams WV.
Correlation of protein and gene expression profiles of inflammatory
proteins after endotoxin challenge in human subjects. DNA Cell Biol 24:
410–431, 2005.
41. Preas HL 2nd, Jubran A, Vandivier RW, Reda D, Godin PJ, Banks
SM, Tobin MJ, and Suffredini AF. Effect of endotoxin on ventilation
and breath variability: role of cyclooxygenase pathway. Am J Respir Crit
Care Med 164: 620–626, 2001.
42. Preas HL 2nd, Nylen ES, Snider RH, Becker KL, White JC, Agosti
JM, and Suffredini AF. Effects of anti-inflammatory agents on serum
levels of calcitonin precursors during human experimental endotoxemia.
J Infect Dis 184: 373–376, 2001.
43. Reiner A, Yekutieli D, and Benjamini Y. Identifying differentially
expressed genes using false discovery rate controlling procedures. Bioin-
formatics 19: 368–375, 2003.
44. Staudt LM. Gene expression physiology and pathophysiology of the
immune system. Trends Immunol 22: 35–40, 2001.
45. Staudt LM and Brown PO. Genomic views of the immune system*.
Annu Rev Immunol 18: 829–859, 2000.
46. Suffredini AF, Fromm RE, Parker MM, Brenner M, Kovacs JA,
Wesley RA, and Parrillo JE. The cardiovascular response of normal
humans to the administration of endotoxin. N Engl J Med 321: 280–287,
1989.
47. Suffredini AF, Hochstein HD, and McMahon FG. Dose-related inflam-
matory effects of intravenous endotoxin in humans: evaluation of a new
clinical lot of Escherichia coli O:113 endotoxin. J Infect Dis 179: 1278–
1282, 1999.
48. Suffredini AF and O’Grady NP. Pathophysiological responses to endo-
toxin in humans. In: Endotoxin in Health and Disease, edited by Brade H,
Opal SM, Vogel SN, and Morrison DC. New York: Marcel Dekker, 1999,
p. 817–830.
49. Teague TK, Hildeman D, Kedl RM, Mitchell T, Rees W, Schaefer BC,
Bender J, Kappler J, and Marrack P. Activation changes the spectrum
but not the diversity of genes expressed by T cells. Proc Natl Acad Sci
USA 96: 12691–12696, 1999.
50. von der Moehlen MAM, Kimmings AN, Wedel NI, Mevissen ML,
Jansen J, Friedmann N, Lorenz TJ, Nelson BJ, White ML, Bauer R,
Hack CE, Eerenberg AJM, and Van Deventer SJH. Inhibition of
endotoxin-induced cytokine release and neutrophil activation in humans
by use of recombinant bactericidal/permeability-increasing protein. J In-
fect Dis 172: 144–151, 1995.
51. Wolff SM, Rubenstein M, Mulholland JH, and Alling DW. Compari-
son of hematologic and febrile response to endotoxin in man. Blood 26:
190–201, 1965.
215
GENE EXPRESSION AFTER HUMAN ENDOTOXIN CHALLENGE
Physiol Genomics • VOL 25 • www.physiolgenomics.org
on May 18, 2011
physiolgenomics.physiology.org
Downloaded from