Monocytes play a pivotal role in various human infectious and inflammatory diseases. To reveal a whole picture of pathophysiologic function of activated human monocytes, this study used the serial analysis of gene expression (SAGE) procedure in lipopolysaccharide (LPS)-stimulated human monocytes. A total of 35 874 tags corresponding to more than 12 000 different transcripts were sequenced. Comparison of gene expression profile with that of resting monocytes revealed the LPS-inducible gene expression profile. Many cytokines and chemokines, including interleukin (IL)-6, IL-1α, IL-1β, tumor necrosis factor (TNF)-α, macrophage inflammatory protein (MIP)-1β, MIP-2β, MIP-2α, liver and activation-regulated chemokine (LARC), MIP-1α, thymus and activation-regulated chemokine (TARC), macrophage-derived chemokine (MDC), regulated on activation, normal T cell expressed and secreted (RANTES), growth-regulated oncogene (GRO) α, and IL-8, were observed in the highest inducible transcripts. Other genes encoding plasminogen activator inhibitor type 2 (PAI-2), Hc-gp39, apolipoproteins, malate dehydrogenase, matrix metalloproteinase-9 (MMP-9), and cyclooxygenase (COX2) were also highly elevated in LPS-stimulated monocytes. Moreover, up-regulation of Naf1β, IL-7 receptor, adenosine receptor A2a, and many novel genes was newly identified. These results suggest that the LPS-inducible gene products may be involved in cell activation and migration, angiogenesis, tissue remodeling, and metabolism, and thus may orchestrate the inflammatory reactions. On the other hand, the expression of numerous sets of novel genes was discovered to be down-regulated on LPS stimulation. This study represents the first comprehensive analysis of LPS-inducible gene expression in human monocytes and provides tremendous novel information for the function of LPS-activated monocytes and targets for diagnosing, monitoring, and treating sepsis and various human infectious and inflammatory diseases.

Introduction

Sepsis is now a contributing factor in more than 100 000 deaths per year in the United States and the annual incidence is nearly 300 000 cases.1,2 In general, the septic response occurs when an invading microbe has circumvented the innate and acquired immune defenses. Lipopolysaccharide (LPS, also called endotoxin), a component of the outer membrane of gram-negative bacteria, is the most potent and well-characterized gram-negative bacterial signal molecule. LPS interacts with CD14 together with Toll-like receptor (Tlr) molecule(s),3-6 a receptor complex on monocytes/macrophages and neutrophils, and activates second messenger and signal transduction pathways. These signals in turn activate transcription factors, mainly nuclear factor (NF)-κB. As a result, LPS triggers a wide variety of cellular responses, including the production of cytokines and chemokines, release of arachidonic acid metabolites, and generation of reactive oxygen and nitrogen intermediates that are responsible for the pathophysiologic reactions.2,7-9 Monocytes play an essential role in infection and inflammation by producing these mediators. Although many LPS-inducible genes have been investigated, no comprehensive study of gene expression in LPS-stimulated monocytes has been reported.

Several methods such as subtractive hybridization10 and differential display11 have been developed to identify changes in expression profiles under different conditions. However, these methods could analyze very limited numbers of transcripts and did not provide the quantitative information. In contrast, the serial analysis of gene expression (SAGE)12-18 is a technique that allows a rapid, detailed analysis of thousands of transcripts simultaneously. This method can be used not only to characterize quantitative information on the abundance of known transcripts but also to identify novel expressed genes. We have recently reported the results of the SAGE technique with human monocytes and macrophages19 and monocyte-derived dendritic cells.20 In this study, we performed SAGE on human blood monocytes and LPS-stimulated monocytes to evaluate the general patterns of gene expression following LPS stimulation.

Materials and methods

Purification of human monocytes

Peripheral blood mononuclear cells (PBMCs) were obtained from the venous blood drawn from 8 healthy volunteers in Tokyo Metropolitan Red Cross Blood Center and were used to prepare human monocytes. PBMCs were isolated by centrifugation on a Ficoll-Metrizoate density gradient (d = 1.077 g/mL, Lymphoprep; Nycomed, Oslo, Norway) and were suspended in RPMI 1640 medium containing 10% FCS (heat-inactivated fetal calf serum, Gibco, Gaithersburg, MD), 100 μg/mL streptomycin, and 100 U/mL penicillin. This medium contained less than 3 pg of LPS per milliliter as assessed by a Limulus amebocyte lysate. PBMCs were then incubated with anti-CD14 monoclonal antibody coated with microbeads, and monocytes were isolated by passing the PBMCs through a magnetic cell separation system (MACS; Miltenyi Biotec, Bergish Gladbach, Germany) with column type VR. The total number of isolated monocytes was 3 × 108. The highly purified monocytes were obtained after the incubation on the plastic tissue culture plate for 30 minutes at 37°C, 5% CO2 in air. More than 99% of the cells were judged to be monocytes by morphology, positive staining for CD14 (LeuM3, Becton Dickinson, San Jose, CA) in a flow cytometric analysis, and nonspecific esterase staining.20To prepare LPS-stimulated monocytes, the freshly isolated monocytes were incubated with 1 μg/mL of LPS (Escherichia coliO55:B5, Difco, Detroit, MI) in RPMI 1640 medium containing 10% FCS in 5% CO2 at 37°C for 3 hours. Monocytes and LPS-stimulated monocytes were prepared from 8 donors.

SAGE protocol

The total RNA of the stimulated cells was isolated by direct lysis using RNAzol B (Cinna/Biotex Laboratories, TEL-TEST, Friendswood, TX). Poly(A)+RNA was further isolated using the FastTrac messenger RNA (mRNA) purification kit (Invitrogen, Carlsbad, CA) according to the manufacturer's instructions. SAGE was performed as described previously.12-15 Poly(A)+RNA (2.5 μg) was converted to double-stranded complementary DNA (cDNA) with a BRL synthesis kit (GIBCO BRL, Rockville, MD) following the manufacturer's protocol with the inclusion of primer biotin-5′-T18-3′. The cDNA was cleaved with NlaIII and the 3′-terminal cDNA fragments were bound to streptoavidin-coated magnetic beads (Dynal, Oslo, Norway). After ligation of oligonucleotides containing recognition sites for BsmFI, the linked cDNAs were released from the beads by digestion with BsmFI. The released tags were ligated to one another, concatenated, and cloned into the SphI site of pZero 1.0 (Invitrogen). Colonies were screened with polymerase chain reaction (PCR) using M13 forward and M13 reverse primers. PCR products containing inserts of more than 400 bp were sequenced with the TaqFS Dyeterminater kit and analyzed using a 377 ABI automated sequencer (Perkin-Elmer, Branchburg, NJ). All electropherograms were reanalyzed by visual inspection to check for ambiguous base and to correct misreads.

The SAGE procedure was performed on mRNA from human monocytes and LPS-stimulated monocytes. Sequence files were analyzed with the SAGE software,12 CGAP SAGE database (http://www.ncbi.nlm.nih.gov/SAGE/), and NCBI's sequence search tool (Advanced BLAST search, http://www.ncbi.nlm.nih.gov/BLAST/). After elimination of linker sequences and the repeated ditags, a total of 93 433 tags representing 57 559 and 35 874 from human monocytes and LPS-stimulated monocytes, respectively, were analyzed. To compare these 2 SAGE libraries, each tag number was normalized using SAGE software12 by calculating each total tag number to 35 800.

Reverse transcriptase-PCR (RT-PCR)

Total RNA (200 ng) was prepared by use of RNAzol B. The RNA was reverse-transcribed in 50 μL of 10 mmol/L Tris-HCl (pH 8.3), 6.5 mmol/L MgCl2, 50 mmol/L KCl, 10 mmol/L dithiothreitol, 1 mmol/L of each dNTP, 2 μmol/L random hexamer, and 2.4 U/μL of Moloney murine leukemia virus reverse transcriptase for 1 hour at 42°C. cDNA, corresponding to 40 ng of total RNA, was boiled for 3 minutes and quenched on ice before amplification by PCR. The conditions for PCR were as follows: in a 50-μL reaction, 0.15 μmol/L of each primer; 125 μmol/L each of dGTP, dATP, dCTP, and dTTP (Toyobo, Osaka, Japan); 50 mmol/L KCl, 10 mmol/L Tris-HCl, pH 8.3; 1.5 mmol/L MgCl2 and AmplyTaq (Perkin-Elmer). Primers used for RT-PCR are listed in Table 1. Reaction mixtures were incubated in a Perkin-Elmer DNA Thermal Cycler for 25 to 30 cycles (denaturation for 60 seconds at 94°C, annealing for 60 seconds at 58°C, extension for 120 seconds at 72°C).

Table 1.

Primers used for RT-PCR

Gene  Primer sequences 
MIP-1β Forward 5′-GAAGCTTCTGAGTTCTGCAGCC-3′ 
 Reverse 5′-TCCTGTCTCTGAGCAGCTCAGT-3′  
EST (AI309978Forward 5′-CTTCGCTGAAGTCATCATGAGC-3′ 
 Reverse 5′-TCCTTATCCAGAGCCCAAAAAA-3′ 
Naf1β Forward 5′-AAATGGAGGAGACCGACAAGG-3′ 
 Reverse 5′-TAGCTGGGCATTTGACAGGGT-3′  
Adenosine receptor A2a Forward 5′-TGTGGCTCAACAGCAACCTG-3′ 
 Reverse 5′-GCATGGACCTCCTTCTGCA-3′  
IFN-inducible protein p78 Forward 5′-CGAGATTGAGATTTCGGATGC-3′ 
 Reverse 5′-TATGTGTGATGAGCTCGCTGG-3′ 
Tristetraprolin Forward 5′-CCCTGATGAATATGCCAGC-3′ 
 Reverse 5′-GGTTCATTGCCTCCCTTAAA-3′ 
PAI-2 Forward 5′-ATTTTGCAGGCACAAGCTGC-3′ 
 Reverse 5′-GCCGAGTTTACACGGAAAGG-3′  
NF-κB p50 Forward 5′-TTGACCTCACTTGCAGCACCT-3′ 
 Reverse 5′-GTACGCACTGTCTTCCTTCACCT-3′ 
LARC Forward 5′-GTTTGCTCCTGGCTGCTTT-3′ 
 Reverse 5′-GTCCAGTGAGGCACAAATTAGA-3′  
IL-7 receptor Forward 5′-AAGCCTATCGTATGGCCCAGT-3′ 
 Reverse 5′-CTGGTACACATGAGGCCCATT-3′ 
MCL1 Forward 5′-GGGCAGGATTGTGACTCTCAT-3′ 
 Reverse 5′-GCTACTGGCCACTTTCCTGTT-3′  
Ferritin H Forward 5′-TACTTTCTTCACCAATCTCATGAG-3′ 
 Reverse 5′-CCCACGGCTATGGGGAAATTAG-3′ 
Gene  Primer sequences 
MIP-1β Forward 5′-GAAGCTTCTGAGTTCTGCAGCC-3′ 
 Reverse 5′-TCCTGTCTCTGAGCAGCTCAGT-3′  
EST (AI309978Forward 5′-CTTCGCTGAAGTCATCATGAGC-3′ 
 Reverse 5′-TCCTTATCCAGAGCCCAAAAAA-3′ 
Naf1β Forward 5′-AAATGGAGGAGACCGACAAGG-3′ 
 Reverse 5′-TAGCTGGGCATTTGACAGGGT-3′  
Adenosine receptor A2a Forward 5′-TGTGGCTCAACAGCAACCTG-3′ 
 Reverse 5′-GCATGGACCTCCTTCTGCA-3′  
IFN-inducible protein p78 Forward 5′-CGAGATTGAGATTTCGGATGC-3′ 
 Reverse 5′-TATGTGTGATGAGCTCGCTGG-3′ 
Tristetraprolin Forward 5′-CCCTGATGAATATGCCAGC-3′ 
 Reverse 5′-GGTTCATTGCCTCCCTTAAA-3′ 
PAI-2 Forward 5′-ATTTTGCAGGCACAAGCTGC-3′ 
 Reverse 5′-GCCGAGTTTACACGGAAAGG-3′  
NF-κB p50 Forward 5′-TTGACCTCACTTGCAGCACCT-3′ 
 Reverse 5′-GTACGCACTGTCTTCCTTCACCT-3′ 
LARC Forward 5′-GTTTGCTCCTGGCTGCTTT-3′ 
 Reverse 5′-GTCCAGTGAGGCACAAATTAGA-3′  
IL-7 receptor Forward 5′-AAGCCTATCGTATGGCCCAGT-3′ 
 Reverse 5′-CTGGTACACATGAGGCCCATT-3′ 
MCL1 Forward 5′-GGGCAGGATTGTGACTCTCAT-3′ 
 Reverse 5′-GCTACTGGCCACTTTCCTGTT-3′  
Ferritin H Forward 5′-TACTTTCTTCACCAATCTCATGAG-3′ 
 Reverse 5′-CCCACGGCTATGGGGAAATTAG-3′ 

Statistical analysis

Statistical significance between samples was calculated as described previously.16 

Results

Results from LPS-stimulated monocytes

In LPS-stimulated monocytes library, a total of 35 874 tags were sequenced. These tags corresponded to more than 12 000 different transcripts. The expressed genes were searched through the GenBank database to identify individual genes. Table2 shows the top 50 transcripts in LPS-stimulated monocytes. The most expressed genes were identified as macrophage inflammatory protein-1α (MIP-1α), with the expression frequency of 3.34%, followed by ferritin L chain and ferritin H chain. Other highly expressed genes consist of products associated with cytokines, chemokines, protein synthesis, lipid metabolism, and major histocompatibility complex (MHC) class I and class II.

Table 2.

Transcripts profile in LPS-stimulated human peripheral blood monocytes

Abundance (%) Tag sequence GenBank match (accession number) 
3.34 GCACCAAAGC MIP1α (D00044)  
1.65 CCCTGGGTTC Ferritin L chain (M11147
1.49 TTGGGGTTTC Ferritin H chain (M97164
0.89 TGTTTTCATA EST (AA777287
0.89 TGGAAGCACT IL-8 (Y00787
0.68 CAAGCATCCC No reliable matches 
0.60 GATAACACAT MIP1β (J04130
0.57 GTTCACATTA CD74, HLA-DR invariant chain p33
(X00497)  
0.54 CCCATCGTCC No reliable matches 
0.52 CCTGTAATCC Multiple matches 
0.51 TTGGTCCTCT Ribosomal protein L41 (AF026844
0.51 CACCTAATTG No reliable matches 
0.50 TGTGTTGAGA Elongation factor 1 α subunit (M27364)  
0.49 CAATTTGTGT IL-1β (K02770
0.49 TGGCCCCAGG Apolipoprotein C-1 (NM001645) 
0.47 GTTGTGGTTA β-2 microglobulin (AB021288
0.46 TAGCCCCCTG TNF (M10988
0.42 CTAAGACTTC No reliable matches 
0.42 CGACCCCACG Apolipoprotein E (M12529
0.42 GTGAAACCCC Multiple matches 
0.42 AGCCCTACAA No reliable matches 
0.39 CCCGTCCGGA Ribosomal protein L13 (AA010823
0.37 GGGCATCTCT HLA-DR α chain (V00523
0.36 TAGGTTGTCT Translationally controlled tumor protein
(X16064)  
0.36 GTGCACTGAG Multiple matches  
0.36 GGCACCTCAG IL-6 (M14584
0.34 CTGACCTGTG MHC class I (M28205
0.34 TTGGTGAAGG Thymosin β-4 (M17733
0.33 TTCATACACC No reliable matches 
0.32 CCACTGCACT Multiple matches 
0.31 TGGGTGAGCC Cathepsin B (L16510
0.31 ACCCTTGGCC No reliable matches 
0.30 TGCCTGCACC Cystatin C (X05607
0.29 CCCTTCTGTA PAI-2 (Y00630
0.28 TAACAGCCAG MAD-3 (M69043
0.27 TGCACGTTTT Ribosomal protein L32 (X03342
0.27 AGGCTACGGA Multiple matches 
0.27 AGGGCTTCCA Wilm's tumor–related protein
(QM) (M64241)  
0.27 GTGCGCTGAG HLA class IC (X58536
0.26 GGATTTGGCC Multiple matches 
0.26 ACTTTTTCAA Multiple matches 
0.26 CACAAACGGT Ribosomal protein S27 (L19739
0.26 GGGCTGGGGT Multiple matches 
0.25 AGCACCTCCA Elongation factor 2 (Z11692
0.23 CTCATAAGGA No reliable matches 
0.23 CCGTCCAAGG Ribosomal protein S16 (M60854
0.23 CCAGAACAGA Multiple matches 
0.23 AAGACAGTGG Ribosomal protein L37a (L06499
0.23 TCCAAATCGA Vimentin (M25246
0.23 GGGGAAATCG Thymosin β10 (M92381
Abundance (%) Tag sequence GenBank match (accession number) 
3.34 GCACCAAAGC MIP1α (D00044)  
1.65 CCCTGGGTTC Ferritin L chain (M11147
1.49 TTGGGGTTTC Ferritin H chain (M97164
0.89 TGTTTTCATA EST (AA777287
0.89 TGGAAGCACT IL-8 (Y00787
0.68 CAAGCATCCC No reliable matches 
0.60 GATAACACAT MIP1β (J04130
0.57 GTTCACATTA CD74, HLA-DR invariant chain p33
(X00497)  
0.54 CCCATCGTCC No reliable matches 
0.52 CCTGTAATCC Multiple matches 
0.51 TTGGTCCTCT Ribosomal protein L41 (AF026844
0.51 CACCTAATTG No reliable matches 
0.50 TGTGTTGAGA Elongation factor 1 α subunit (M27364)  
0.49 CAATTTGTGT IL-1β (K02770
0.49 TGGCCCCAGG Apolipoprotein C-1 (NM001645) 
0.47 GTTGTGGTTA β-2 microglobulin (AB021288
0.46 TAGCCCCCTG TNF (M10988
0.42 CTAAGACTTC No reliable matches 
0.42 CGACCCCACG Apolipoprotein E (M12529
0.42 GTGAAACCCC Multiple matches 
0.42 AGCCCTACAA No reliable matches 
0.39 CCCGTCCGGA Ribosomal protein L13 (AA010823
0.37 GGGCATCTCT HLA-DR α chain (V00523
0.36 TAGGTTGTCT Translationally controlled tumor protein
(X16064)  
0.36 GTGCACTGAG Multiple matches  
0.36 GGCACCTCAG IL-6 (M14584
0.34 CTGACCTGTG MHC class I (M28205
0.34 TTGGTGAAGG Thymosin β-4 (M17733
0.33 TTCATACACC No reliable matches 
0.32 CCACTGCACT Multiple matches 
0.31 TGGGTGAGCC Cathepsin B (L16510
0.31 ACCCTTGGCC No reliable matches 
0.30 TGCCTGCACC Cystatin C (X05607
0.29 CCCTTCTGTA PAI-2 (Y00630
0.28 TAACAGCCAG MAD-3 (M69043
0.27 TGCACGTTTT Ribosomal protein L32 (X03342
0.27 AGGCTACGGA Multiple matches 
0.27 AGGGCTTCCA Wilm's tumor–related protein
(QM) (M64241)  
0.27 GTGCGCTGAG HLA class IC (X58536
0.26 GGATTTGGCC Multiple matches 
0.26 ACTTTTTCAA Multiple matches 
0.26 CACAAACGGT Ribosomal protein S27 (L19739
0.26 GGGCTGGGGT Multiple matches 
0.25 AGCACCTCCA Elongation factor 2 (Z11692
0.23 CTCATAAGGA No reliable matches 
0.23 CCGTCCAAGG Ribosomal protein S16 (M60854
0.23 CCAGAACAGA Multiple matches 
0.23 AAGACAGTGG Ribosomal protein L37a (L06499
0.23 TCCAAATCGA Vimentin (M25246
0.23 GGGGAAATCG Thymosin β10 (M92381

Top 50 transcripts expressed in LPS-stimulated monocytes are listed.

The tag sequence represents the 10-bp SAGE tag. Probable GenBank matches are listed.

More information on this table is available at our web site (http://www.prevent.m.u-tokyo.ac.jp/SAGE.html).

Comparison of gene expression profile between resting and LPS-stimulated monocytes

We previously reported results of SAGE on human monocytes and macrophages.19 To investigate the LPS-stimulation regulated genes in human monocytes, we compared the unstimulated19 and stimulated SAGE tag libraries after normalization of each tag number using SAGE software.12Comparison of expression patterns revealed that most genes (> 20 000 transcripts) were expressed at similar levels between resting monocytes and LPS-stimulated monocytes (Figure 1). However, the expression profiles also revealed 250 transcripts that were expressed at significantly different levels (P < .01). Expression levels of 132 of 250 genes were decreased in LPS-stimulated monocytes as compared with those in unstimulated monocytes. Conversely, 118 transcripts were overexpressed in LPS-stimulated monocytes.

Fig. 1.

Comparison of gene expression patterns in resting and LPS-stimulated monocytes.

A semilogarithmic plot reveals 40 tags that were decreased more than 10-fold in LPS-stimulated monocytes, whereas 60 tags were increased more than 10-fold. After normalization of the number of each tag, the relative expression of each transcript was determined by dividing the number of tags observed in monocytes or LPS-stimulated monocytes as indicated. To avoid division by 0, we used a tag value 1 for any tag that was not detectable in one of the samples. These ratios are plotted on the abscissa. The number of genes displaying each ratio is plotted on the ordinate. Mono and LPS indicate resting monocytes and LPS-stimulated monocytes, respectively.

Fig. 1.

Comparison of gene expression patterns in resting and LPS-stimulated monocytes.

A semilogarithmic plot reveals 40 tags that were decreased more than 10-fold in LPS-stimulated monocytes, whereas 60 tags were increased more than 10-fold. After normalization of the number of each tag, the relative expression of each transcript was determined by dividing the number of tags observed in monocytes or LPS-stimulated monocytes as indicated. To avoid division by 0, we used a tag value 1 for any tag that was not detectable in one of the samples. These ratios are plotted on the abscissa. The number of genes displaying each ratio is plotted on the ordinate. Mono and LPS indicate resting monocytes and LPS-stimulated monocytes, respectively.

Table 3 lists the 50 most highly expressed tags in LPS-stimulated monocytes. These LPS-induced transcripts mainly consist of genes encoding proteins associated with cytokines and chemokines including interleukin (IL)-6, IL-1α, IL-1β, tumor necrosis factor (TNF), MIP-1β, MIP-2β, MIP-2α, liver and activation-regulated chemokine (LARC), thymus and activation-regulated chemokine (TARC), macrophage-derived chemokine (MDC), regulated on activation, normal T cell expressed and secreted (RANTES), and growth-regulated oncogene α (GRO α); lipid metabolism such as apolipoprotein C-1, apolipoprotein E, and lysosomal acid lipase; and proteases and inhibitors such as plasminogen activator inhibitor type 2 (PAI-2), matrix metalloproteinase-9 (MMP-9), and cystatin B.

Table 3.

Transcripts increased in LPS-stimulated monocytes

Fold Tag sequences No. GenBank match (accession number) 
Mono LPS 
128 GGCACCTCAG 128 IL-6 (M14584)  
108 GATAACACAT 215 MIP1β (J04130
105 CCCTTCTGTA 105 PAI-2 (Y00630
66 ACTGTGGCGG 66 EST (AI309978
44 TGGCCCCAGG 177 Apolipoprotein C-1 (NM001645)  
38 CGACCCCACG 152 Apolipoprotein E (M12529)  
35 TGTTTTCATA 318 EST (AA777287
31 GTATGGGCCC 31 Hc-gp39 (M80927
30 ATAATAAAAG 30 MIP2β/GROγ (M36821
30 CTGTTAGTGT 30 Malate dehydrogenase 1 (D55654)  
30 TTGAAGCTTT 30 MIP2α/GROβ (M36820)  
28 GGGAAGGGGA 28 EST (AA554342
28 TAAATCCCCA 28 MMP9/collagenase type IV (J05070)  
25 AGACCACTGT 25 IL-1α (X02851
25 GAGCGGCACC 25 No reliable matches 
24 GCCACACCCA 24 EST (AI825483
23 CACCTCCTAT 23 No reliable matches 
22 GAGGCCCACA 22 No reliable matches 
22 TCACCGGTCA 22 Gelsolin (X04412
21 CCCTGGATCC 21 Multiple matches 
21 GGAAGGGGAG 21 NF-κB p50 (X61498
20 GTCTTAAGCA 20 EST (AI337038
20 CAATTTGTGT 177 IL-1β (K02770
19 GAGGGTTTAG 19 LARC (D86955
19 CAAGCATCCC 13 243 No reliable matches 
18 GCACCAAAGC 66 1195  MIP1α (D00044)  
18 TGAAGCACTT 18 Multiple matches 
17 GGCACAAAGG 17 TARC (D43767
17 AGAAGTGTCC 17 Lysosomal acid lipase A (Z31690)  
16 AGTCTTGCCG 16 No reliable matches 
16 TGGATTTGGT 16 IL-7 receptor (M29696
16 GACATAAATC 16 Naf1β (AJ011896
15 TAGCCCCCTG 11 166 TNF (M10988
15 GCTTGCAAAA 60 MnSOD (M36693
14 CAGCTATTTC 14 PA-FABP (M94856
14 GCCCCTGCGC 14 No reliable matches 
14 ACCACTTATC 14 EST (AA865837
14 TGCTGAGTAG 14 Adenosine receptor A2a (S46950)  
13 AATCTGCGCC 53 IFN-stimulated protein, 15kD (M13755)  
13 AACGGGGCCC 13 MDC (U83171)  
12 ATGAGCTGAC 48 Cystatin B (L03558
12 AAAAATCGGC 12 RANTES (AA486072
12 TTGAAACTTT 12 GROα (J03561
12 CTGTTCCTTT 12 Cyclooxygenase 2 (COX2) (M90100)  
12 TCTGAAGTCA 12 EST (AA432060
12 GCCCCGGGGG 12 No reliable matches 
12 TATTTTCATA 12 No reliable matches 
12 AGTGCCGTGT 12 IFN-inducible protein p78 (M33882)  
12 TATTTTGTGA 12 Myristoylated alanine-rich protein kinase C substrate/MARCKS (M68956
11 ACTGCCTACA 80 No reliable matches 
Fold Tag sequences No. GenBank match (accession number) 
Mono LPS 
128 GGCACCTCAG 128 IL-6 (M14584)  
108 GATAACACAT 215 MIP1β (J04130
105 CCCTTCTGTA 105 PAI-2 (Y00630
66 ACTGTGGCGG 66 EST (AI309978
44 TGGCCCCAGG 177 Apolipoprotein C-1 (NM001645)  
38 CGACCCCACG 152 Apolipoprotein E (M12529)  
35 TGTTTTCATA 318 EST (AA777287
31 GTATGGGCCC 31 Hc-gp39 (M80927
30 ATAATAAAAG 30 MIP2β/GROγ (M36821
30 CTGTTAGTGT 30 Malate dehydrogenase 1 (D55654)  
30 TTGAAGCTTT 30 MIP2α/GROβ (M36820)  
28 GGGAAGGGGA 28 EST (AA554342
28 TAAATCCCCA 28 MMP9/collagenase type IV (J05070)  
25 AGACCACTGT 25 IL-1α (X02851
25 GAGCGGCACC 25 No reliable matches 
24 GCCACACCCA 24 EST (AI825483
23 CACCTCCTAT 23 No reliable matches 
22 GAGGCCCACA 22 No reliable matches 
22 TCACCGGTCA 22 Gelsolin (X04412
21 CCCTGGATCC 21 Multiple matches 
21 GGAAGGGGAG 21 NF-κB p50 (X61498
20 GTCTTAAGCA 20 EST (AI337038
20 CAATTTGTGT 177 IL-1β (K02770
19 GAGGGTTTAG 19 LARC (D86955
19 CAAGCATCCC 13 243 No reliable matches 
18 GCACCAAAGC 66 1195  MIP1α (D00044)  
18 TGAAGCACTT 18 Multiple matches 
17 GGCACAAAGG 17 TARC (D43767
17 AGAAGTGTCC 17 Lysosomal acid lipase A (Z31690)  
16 AGTCTTGCCG 16 No reliable matches 
16 TGGATTTGGT 16 IL-7 receptor (M29696
16 GACATAAATC 16 Naf1β (AJ011896
15 TAGCCCCCTG 11 166 TNF (M10988
15 GCTTGCAAAA 60 MnSOD (M36693
14 CAGCTATTTC 14 PA-FABP (M94856
14 GCCCCTGCGC 14 No reliable matches 
14 ACCACTTATC 14 EST (AA865837
14 TGCTGAGTAG 14 Adenosine receptor A2a (S46950)  
13 AATCTGCGCC 53 IFN-stimulated protein, 15kD (M13755)  
13 AACGGGGCCC 13 MDC (U83171)  
12 ATGAGCTGAC 48 Cystatin B (L03558
12 AAAAATCGGC 12 RANTES (AA486072
12 TTGAAACTTT 12 GROα (J03561
12 CTGTTCCTTT 12 Cyclooxygenase 2 (COX2) (M90100)  
12 TCTGAAGTCA 12 EST (AA432060
12 GCCCCGGGGG 12 No reliable matches 
12 TATTTTCATA 12 No reliable matches 
12 AGTGCCGTGT 12 IFN-inducible protein p78 (M33882)  
12 TATTTTGTGA 12 Myristoylated alanine-rich protein kinase C substrate/MARCKS (M68956
11 ACTGCCTACA 80 No reliable matches 

The 50 transcripts displaying the largest increase in expression in LPS-stimulated monocytes are listed by fold induction.

The tag sequence represents the 10-bp SAGE tag. The most probable GenBank matches are listed.

Each tag number was normalized using SAGE software by calculating the total tag number to 35 800.

No. indicates the number of times the tag was identified. Fold change in expression was calculated as described in Figure 1.

Mono and LPS indicate resting and LPS-stimulated monocytes, respectively.

More information on this table is available at our web site (http://www.prevent.m.u-tokyo.ac.jp/SAGE.html).

Table 4 shows the top 50 transcripts identified to be decreased in LPS-stimulated monocytes. The mRNAs encoding some ribosomal proteins, DNA-binding proteins such as GOS3, c-fos, jun-D, zing finger protein (tristetraprolin), and C/EBPδ, differentiation-related protein such as MCL1, and cell structure-related proteins such as actin-binding protein p57 and ARC41 were decreased.

Table 4.

Transcripts decreased in LPS-stimulated monocytes

Fold Tag sequences No. GenBank match (accession number) 
Mono LPS 
39 CTGATGGCGA 39 EST (AA587283)  
34 CTGTACTTGT 34 GOS3 (L49169
32 TGGAAAGTGA 32 c-fos (NM005252) 
30 GGGAAACAGG 30 EST (AA157963
26 TACATTCTGT 26 MCL1 (L08246
24 TGGAGAAGAG 24 EST (AA521075
22 GCGGCTTTCC 22 cDNA homologous to yeast SCO1 (AL021683)  
19 GCAGAGAAAA 19 Coronin, actin-binding, 1A (D44497
19 AGTGCACGTG 19 EST (AA157635
19 TTCATAGCTG 19 Cartilage-associated protein (CASP) (AJ006470)  
18 ATCAAGTTCG 18 EST (AI343440)  
17 GTGGGTTGGC 17 Aldehyde dehydrogenase 2 (K03001
16 GGCCTTTTTT 32 Histone H1x (D64142
16 CCCCCTGCCC 16 EST (AA031810
16 GTGGGCCACG 16 No reliable matches 
15 TGGTACACGT 15 EST (AA132037
15 GGGCCAGGGG 15 EST (AA178975
14 TCAGAGATGA 14 Syntaxin-binding protein 2 (AB002559)  
14 TCCGCGAGAA 14 EST (AA045234
14 GCTGTTGCGC 41 EST (AA076625
13 AATTAAATTA 13 No reliable matches 
13 ACCATTCTGC 13 Interferon-inducible gene I-8D (X57351)  
13 GGGGGCGCCT 13 EST (AA133899
13 GCCGCCGTGC 13 No reliable matches 
13 TGAAGGAGCC 25 ATP synthase subunit C (M16439)  
12 CTTGGGATGT 12 EST (AA074076
12 TGCACCACAG 12 Signal peptidase complex (AF061737)  
12 AAGAAGACTT 12 GABA(A) receptor-associated protein (NM007278) 
12 AGTATCTGGG 12 Actin-related protein 2/3 complex, subunit 1B (AF006084
12 CCCACACTAC 12 Multiple matches 
12 GCTCAGCTGG 12 EST (AA053346
11 GCCGCCATCT 44 Transketolase (L12711
11 GAGAAATCGT 11 Lysozyme (M21119
11 TAATGCTAAA 11 GOS8 (L13463
11 TCGCCGCGAC 11 No reliable matches 
11 ACGCTCTCGA 11 CD37 (X14046
11 GTGCCCGTGC 11 EST (AA074032
11 TCTGGTCTGG 11 Flotillin 2 (NM004475) 
11 TGAACCCGGG 11 EST (AA515326
11 TTGGAGCACT 11 EST (AA724726
10 TACCTGCAGA 180 18 Calgranulin A (X06234
10 ACCCCCCCGC 60 Jun D (X51346
10 TCTACACGTG 39 Properdin P factor (M83652
10 GGCCAGGACT 19 N-formyl peptide receptor (M60627)  
ATGGTGGGGG 27 Tristetraprolin (M63625)  
ACTACAAATA EST (AW169101
CTCACTTTTT C/EBPδ/NF-IL6 β (M83667
GCCTGGCCAT Multiple matches 
GGTAGAACTA EST (AA234724
GTGACTGCCA Multiple matches 
Fold Tag sequences No. GenBank match (accession number) 
Mono LPS 
39 CTGATGGCGA 39 EST (AA587283)  
34 CTGTACTTGT 34 GOS3 (L49169
32 TGGAAAGTGA 32 c-fos (NM005252) 
30 GGGAAACAGG 30 EST (AA157963
26 TACATTCTGT 26 MCL1 (L08246
24 TGGAGAAGAG 24 EST (AA521075
22 GCGGCTTTCC 22 cDNA homologous to yeast SCO1 (AL021683)  
19 GCAGAGAAAA 19 Coronin, actin-binding, 1A (D44497
19 AGTGCACGTG 19 EST (AA157635
19 TTCATAGCTG 19 Cartilage-associated protein (CASP) (AJ006470)  
18 ATCAAGTTCG 18 EST (AI343440)  
17 GTGGGTTGGC 17 Aldehyde dehydrogenase 2 (K03001
16 GGCCTTTTTT 32 Histone H1x (D64142
16 CCCCCTGCCC 16 EST (AA031810
16 GTGGGCCACG 16 No reliable matches 
15 TGGTACACGT 15 EST (AA132037
15 GGGCCAGGGG 15 EST (AA178975
14 TCAGAGATGA 14 Syntaxin-binding protein 2 (AB002559)  
14 TCCGCGAGAA 14 EST (AA045234
14 GCTGTTGCGC 41 EST (AA076625
13 AATTAAATTA 13 No reliable matches 
13 ACCATTCTGC 13 Interferon-inducible gene I-8D (X57351)  
13 GGGGGCGCCT 13 EST (AA133899
13 GCCGCCGTGC 13 No reliable matches 
13 TGAAGGAGCC 25 ATP synthase subunit C (M16439)  
12 CTTGGGATGT 12 EST (AA074076
12 TGCACCACAG 12 Signal peptidase complex (AF061737)  
12 AAGAAGACTT 12 GABA(A) receptor-associated protein (NM007278) 
12 AGTATCTGGG 12 Actin-related protein 2/3 complex, subunit 1B (AF006084
12 CCCACACTAC 12 Multiple matches 
12 GCTCAGCTGG 12 EST (AA053346
11 GCCGCCATCT 44 Transketolase (L12711
11 GAGAAATCGT 11 Lysozyme (M21119
11 TAATGCTAAA 11 GOS8 (L13463
11 TCGCCGCGAC 11 No reliable matches 
11 ACGCTCTCGA 11 CD37 (X14046
11 GTGCCCGTGC 11 EST (AA074032
11 TCTGGTCTGG 11 Flotillin 2 (NM004475) 
11 TGAACCCGGG 11 EST (AA515326
11 TTGGAGCACT 11 EST (AA724726
10 TACCTGCAGA 180 18 Calgranulin A (X06234
10 ACCCCCCCGC 60 Jun D (X51346
10 TCTACACGTG 39 Properdin P factor (M83652
10 GGCCAGGACT 19 N-formyl peptide receptor (M60627)  
ATGGTGGGGG 27 Tristetraprolin (M63625)  
ACTACAAATA EST (AW169101
CTCACTTTTT C/EBPδ/NF-IL6 β (M83667
GCCTGGCCAT Multiple matches 
GGTAGAACTA EST (AA234724
GTGACTGCCA Multiple matches 

The 50 transcripts displaying the largest decrease in expression in LPS-stimulated monocytes are listed by fold reduction.

The tag sequence represents the 10-bp SAGE tag. The most probable GenBank matches are listed.

Each tag number was normalized using SAGE software by calculating the total tag number to 35 800.

No. indicates the number of times the tag was identified. Fold change in expression was calculated as described in Figure 1.

Mono and LPS indicate resting and LPS-stimulated monocytes, respectively.

More information on this table is available at our web site (http://www.prevent.m.u-tokyo.ac.jp/SAGE.html).

RT-PCR of genes represented in the SAGE

Although we obtained the blood from 8 healthy volunteers to find the average in the gene expression, one question that still arises from these data is if a difference exists in the gene expression among individual donor-derived cells. Another possibility is that the change of gene expression was due merely to cell adhesion to the plastic tissue culture plate.21,22 To address these questions, we arbitrarily selected 6 differentially expressed transcripts and evaluated them in 3 donor-derived samples of unstimulated, incubated for 3 hours without LPS-stimulation, and LPS-stimulated monocytes by RT-PCR (Figure 2A). The expression of each transcript was compared to SAGE data (Tables 3 and 4). MIP-1β (resting monocytes [Mo] 2:LPS-stimulated monocytes [LPS] 215), EST (AI309 978) (Mo 1:LPS 66), Naf1β (Mo 1:LPS 16), adenosine receptor A2a (Mo 1:LPS 14), and interferon (IFN)-inducible protein p78 were highly induced (Mo 1:LPS 12); whereas tristetraprolin (Mo 27:LPS 3) was reduced and ferritin H was expressed almost equally (Mo 471:LPS 534). Although there were some different expression levels of transcripts among the donors, it was confirmed that the induction of the identified genes was due to the specific stimulation of LPS rather than simple adhesion. Moreover, we selected 5 differentially expressed transcripts and examined the time course of the induction of these genes after LPS stimulation (Figure 2B). The expression of the genes encoding PAI-2 (Mo 0:LPS 105), NF-κB p50 (Mo 1:LPS 21), LARC (Mo 0:LPS 19), and IL-7 receptor (IL-7R) (Mo 0:LPS 16) was highly induced up to 12 hours, but that of NF-κB p50 and LARC was barely detected at 24 hours, whereas the expression of MCL1 gene was gradually decreased (Mo 26:LPS 0). These results validate our SAGE data for resting and LPS-stimulated monocytes and establish the general expression profiles of the LPS-inducible genes in human monocytes.

Fig. 2.

RT-PCR analysis of genes expressed differently in resting and LPS-stimulated monocytes.

(A) RT-PCR was performed on total RNA isolated from human resting monocytes (1), monocytes only incubated for 3 hours without LPS (2), and monocytes cultured for 3 hours with LPS (3), as described in Materials and methods. A, B, and C indicate different donors. Mono and LPS indicate resting monocytes and LPS-stimulated monocytes, respectively. SAGE tag No. is the number of times the tag was identified as shown in Tables 3 and 4. (B) Monocytes were incubated with LPS for 0, 1, 3, 6, 12, 24 hours, respectively, and RT-PCR was performed on these samples from 3 different donor-derived cells. A representative result is shown.

Fig. 2.

RT-PCR analysis of genes expressed differently in resting and LPS-stimulated monocytes.

(A) RT-PCR was performed on total RNA isolated from human resting monocytes (1), monocytes only incubated for 3 hours without LPS (2), and monocytes cultured for 3 hours with LPS (3), as described in Materials and methods. A, B, and C indicate different donors. Mono and LPS indicate resting monocytes and LPS-stimulated monocytes, respectively. SAGE tag No. is the number of times the tag was identified as shown in Tables 3 and 4. (B) Monocytes were incubated with LPS for 0, 1, 3, 6, 12, 24 hours, respectively, and RT-PCR was performed on these samples from 3 different donor-derived cells. A representative result is shown.

More information on this work is available at our web site (http://www.prevent.m.u-tokyo.ac.jp/SAGE.html).

Discussion

Experimental and clinical studies have provided details about a series of expressions and mechanisms of action of LPS-inducible gene products.7 However, these studies provided only the limited number of the well-known mediators and the global quantitative analysis of gene expression has never been conducted. In this study, we have applied the recently developed SAGE method to allow quantitative analysis of a large number of transcripts in human LPS-stimulated monocytes.

Among thousands of differentially expressed genes, many cytokine and chemokine genes were identified to be highly inducible as expected. The widely studied proinflammatory cytokines, IL-1, IL-6, and TNF, were expressed at higher levels in LPS-stimulated monocytes than resting cells and should play a central role in the initiation of systemic responses (Table 3 and the categorized list in Table5). Chemokines are small proteins with 4 conserved cysteines forming 2 essential disulfide bonds. Four subfamilies, CXC, CC, C, and CX3C chemokines, are distinguished according to the position of the first 2 cysteines. Now chemokine functions extend far beyond leukocyte physiology and include leukocyte trafficking, viral infection, angiogenesis, hematopoiesis, and antitumor effects.23,24 Surprisingly, many chemokines were up-regulated simultaneously on LPS-stimulation. Among them, CC chemokines, including MIP-1β, LARC, MIP-1α, TARC, MDC, RANTES (Table 3 and the categorized list in Table 5), monocyte chemoattractant protein-1 (MCP-1), and MCP-2 (Table 5), were highly induced. These CC chemokines mainly chemoattract monocytes, basophils, eosinophils, and lymphocytes. The other major chemokine subfamily, CXC chemokines, including MIP-2β (GRO γ), MIP-2α (GRO β), GRO α (Tables 3 and5), and IL-8 (Tables 2 and 5), were also increased. Interestingly, all these highly inducible CXC chemokines belong to the subgroup called ELR chemokines, which have a 3-amino acid motif, ELR (glutamate-leucin-arginine) between the N-terminus and the first cysteine. These ELR CXC chemokines have an apparent uniformity of function such as neutrophil chemoattractants and activator, endothelial cell chemoattractants, and angiogenic factors. In contrast, non-ELR CXC chemokines inhibit the angiogenic effects of ELR chemokines and basic fibroblast growth factor (bFGF),23 and the transcripts of this subgroup were not increased significantly in LPS-stimulated monocytes. These data suggest that monocytes are involved in inflammatory angiogenesis.25 It was reported that monocytes adhere to the vascular wall during angiogenesis and monocyte activation plays a major role in angiogenesis and collateral artery growth.26 TNF and bFGF were presumed to be involved in this event.27-29 However, in addition to these factors, our results showed other mediators such as ELR CXC chemokines might contribute to the inflammatory angiogenesis. Moreover, these results indicate that a wide variety of chemokines may orchestrate under pathophysiologic conditions and play a role in inflammatory reactions.

Table 5.

Categorized transcripts highly expressed or increased in LPS-stimulated monocytes

Fold Tag sequences No. GenBank match
(accession number) 
Mono LPS  
Cytokines and cytokine receptors 
128 GGCACCTCAG 128 IL-6 (M14584)  
25 AGACCACTGT 25 IL-1α (X02851
20 CAATTTGTGT 177 IL-1β (K02770
15 TAGCCCCCTG 11 166 TNF (M10988
16 TGGATTTGGT 16 IL-7 receptor (M29696
Chemokines  
 CC 
108 GATAACACAT 215 MIP1β (J04130
19 GAGGGTTTAG 19 LARC (D86955
18 GCACCAAAGC 66 1 195  MIP1α (D00044)  
17 GGCACAAAGG 17 TARC (D43767
13 AACGGGGCCC 13 MDC (U83171
12 AAAAATCGGC 12 RANTES (AA486072
GTACTAGTGT MCP-1 (M24545
GATCATCAAG MCP-2 (Y10802
 CXC 
30 ATAATAAAAG 30 MIP2β/GROγ (M36821
30 TTGAAGCTTT 30 MIP2α/GROβ (M36820
12 TTGAAACTTT 12 GROα (J03561
TGGAAGCACT 60 317 IL-8 (Y00787
Proteases and protease inhibitors 
105 CCCTTCTGTA 105 PAI-2 (Y00630
28 TAAATCCCCA 28 MMP9/collagenase type IV
(J05070
TGGGTGAGCC 24 112 Cathepsin B (L16510
0.8 TGCCTGCACC 130 108 Cystatin C (X05607
Lipid metabolism 
44 TGGCCCCAGG 177 Apolipoprotein C-1 (NM001645)  
38 CGACCCCACG 152 Apolipoprotein E (M12529)  
17 AGAAGTGTCC 17 Lysosomal acid lipase A (Z31690)  
Transcriptional factors 
21 GGAAGGGGAG 21 NF-κB p50 (X61498
10 ATTATGGGCA 10 NF-κB p105 (M55643
Iron homeostasis 
CCCTGGGTTC 355 591 Ferritin L chain (M11147
TTGGGGTTTC 471 534 Ferritin H chain (M97164
Antigen presentation 
0.9 GTTCACATTA 230 203 CD74, HLA-DR invariant chain
p33 (X00497
GTTGTGGTTA 170 169 β-2 microglobulin (AB021288)  
0.8 GGGCATCTCT 161 131 HLA-DR α chain (V00523)  
0.6 CTGACCTGTG 220 122 MHC class I (M28205)  
0.9 GTGCGCTGAG 108 96 HLA class IC (X58536
Fold Tag sequences No. GenBank match
(accession number) 
Mono LPS  
Cytokines and cytokine receptors 
128 GGCACCTCAG 128 IL-6 (M14584)  
25 AGACCACTGT 25 IL-1α (X02851
20 CAATTTGTGT 177 IL-1β (K02770
15 TAGCCCCCTG 11 166 TNF (M10988
16 TGGATTTGGT 16 IL-7 receptor (M29696
Chemokines  
 CC 
108 GATAACACAT 215 MIP1β (J04130
19 GAGGGTTTAG 19 LARC (D86955
18 GCACCAAAGC 66 1 195  MIP1α (D00044)  
17 GGCACAAAGG 17 TARC (D43767
13 AACGGGGCCC 13 MDC (U83171
12 AAAAATCGGC 12 RANTES (AA486072
GTACTAGTGT MCP-1 (M24545
GATCATCAAG MCP-2 (Y10802
 CXC 
30 ATAATAAAAG 30 MIP2β/GROγ (M36821
30 TTGAAGCTTT 30 MIP2α/GROβ (M36820
12 TTGAAACTTT 12 GROα (J03561
TGGAAGCACT 60 317 IL-8 (Y00787
Proteases and protease inhibitors 
105 CCCTTCTGTA 105 PAI-2 (Y00630
28 TAAATCCCCA 28 MMP9/collagenase type IV
(J05070
TGGGTGAGCC 24 112 Cathepsin B (L16510
0.8 TGCCTGCACC 130 108 Cystatin C (X05607
Lipid metabolism 
44 TGGCCCCAGG 177 Apolipoprotein C-1 (NM001645)  
38 CGACCCCACG 152 Apolipoprotein E (M12529)  
17 AGAAGTGTCC 17 Lysosomal acid lipase A (Z31690)  
Transcriptional factors 
21 GGAAGGGGAG 21 NF-κB p50 (X61498
10 ATTATGGGCA 10 NF-κB p105 (M55643
Iron homeostasis 
CCCTGGGTTC 355 591 Ferritin L chain (M11147
TTGGGGTTTC 471 534 Ferritin H chain (M97164
Antigen presentation 
0.9 GTTCACATTA 230 203 CD74, HLA-DR invariant chain
p33 (X00497
GTTGTGGTTA 170 169 β-2 microglobulin (AB021288)  
0.8 GGGCATCTCT 161 131 HLA-DR α chain (V00523)  
0.6 CTGACCTGTG 220 122 MHC class I (M28205)  
0.9 GTGCGCTGAG 108 96 HLA class IC (X58536

The tag sequence represents the 10-bp SAGE tag. The most probable GenBank matches are listed.

Each tag number was normalized using SAGE software by calculating the total tag number to 35 800.

No. indicates the number of times the tag was identified. Fold change in expression was calculated as described in Figure 1.

Mono and LPS indicate resting and LPS-stimulated monocytes, respectively.

More information on this table is available at our web site (http://www.prevent.m.u-tokyo.ac.jp/SAGE.html).

In contrast, the gene expression of receptors of cytokine and chemokine was not significantly changed after LPS stimulation except for the up-regulation of the IL-7R gene (Table 3 and the categorized list in Table 5). Through the IL-7–induced production of inflammatory cytokines by monocytes,30-32 IL-7R may contribute to inflammation and tumor immunity.30 

Disseminated intravascular coagulation (DIC) is frequently associated with sepsis and can be a life-threatening bleeding disorder.9 LPS is known to activate several steps in the coagulation cascade. The accelerated coagulation reactions cause small thrombi and emboli throughout the microvasculature followed by a phase of procoagulant consumption and secondary fibrinolysis. In this study, PAI-2, a member of the serine protease inhibitor (Serpin) superfamily,33 was one of the highest induced genes in LPS-stimulated monocytes (Table 3 and the categorized list in Table 5). Suppression of the fibrinolytic system directly contributes to the persistence of intravascular clots. PAI-2 is an inhibitor of urokinase-type plasminogen activator (u-PA) and may be involved in fibrinolytic suppression and modulation of DIC. Furthermore, because u-PA generates plasmin in events involving degradation of extracellular matrix,34 PAI-2 may also contribute to fibrin deposition, tissue remodeling, and cell migration at the site of inflammation.

Other known inflammation-related transcripts such as MMP-9 and inducible cyclooxygenase (COX2) were increased on LPS stimulation (Table 3). These results suggest that the proteinase MMP-9 may be involved in local remodeling and repair,35-37 and the enzyme COX2 may play a critical role in inflammation and modulate the systemic reaction by converting arachidonic acid to prostaglandins and thromboxans.38 

Another novel observation is the up-regulation of Naf1β (Nef-associated factor 1β) and adenosine receptor A2a (Table 3). Naf1β is human immunodeficiency virus-1 (HIV-1) Nef-binding protein that increased cell surface CD4 expression.39 The role of Naf1β in LPS-stimulated monocytes remains to be elucidated. Adenosine is a potent endogenous anti-inflammatory agent released by cells under circumstances of metabolic stress, such as ischemia. Currently, at least 4 adenosine receptors, A1, A2a, A2b, and A3, have been identified.40 The increased expression of adenosine receptor A2a is likely to contribute to systemic control of inflammation via local inhibition of the cytokine synthesis.41,42 

In this study, many genes were very unexpectedly found to be decreased on LPS stimulation (Table 4). MCL-1 is a member of the Bcl-2 family expressed in early monocyte differentiation43 and has moderate viability-enhancing effects in a spectrum of hematopoietic cells in transgenic mice.44 The down-regulation of “early differentiation gene” MCL-1 may relate to the activated state of the monocytes rather than differentiated state and to the rapid turnover of the mRNA.43 Immediate early genes such as c-fos, jun-D, andtristetraprolin45 and other DNA binding proteins like GOS3 and C/EBPδ were decreased. Our results suggest that these down-regulated transcripts may control the LPS-induced gene expression transiently to the adequate level. Although the biologic significance of the decreased expression of numerous genes mostly remains to be clarified, this discovery may open a new biologic research field of activated monocytes.

In conclusion, we completed SAGE of LPS-stimulated monocytes. Comparison between resting and activated monocytes revealed the comprehensive LPS-inducible gene expression profiles in monocytes. This study confirms the pivotal role of monocytes with a variety of functions in inflammation, tissue injury and repair, angiogenesis, and metabolism. The data revealed in this study should provide basic information necessary for further understanding of the molecular pathogenesis of sepsis and be useful in diagnosing or monitoring human various infectious and inflammatory diseases in combination with a developing DNA microarray system. Furthermore, tag sequences of unknown genes identified here suffice to clone their cDNAs, and some of these gene products may be useful as pharmaceuticals or targets for novel intervention therapy of inflammatory diseases.

Acknowledgments

We are very grateful to Dr V. E. Velculescu, L. Zhang, W. Zhou, B. Vogelstein, and K. W. Kinzler for their help with the SAGE procedures, and also to Dr H. Young for reviewing this manuscript.

The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 U.S.C. section 1734.

References

References
1
Parrillo
JE
Parker
MM
Natanson
C
et al. 
Septic shock in humans.
Ann Intern Med.
113
1990
227
242
2
Bone
RC
The pathogenesis of sepsis.
Ann Intern Med.
115
1991
457
469
3
Yang
R-B
Mark
MR
Gray
A
et al. 
Toll-like receptor-2 mediates lipopolysaccharide-induced cellular signalling.
Nature
395
1998
284
288
4
Kirschning
CJ
Wesche
H
Ayres
TM
Rothe
M
Human Toll-like receptor 2 confers responsiveness to bacterial lipopolysaccharide.
J Exp Med.
188
1998
2091
2097
5
Poltorak
A
He
X
Smirnova
I
et al. 
Defective LPS signaling in C3H/HeJ and C57BL/10ScCr mice: mutations in Tlr4 gene.
Science.
282
1998
2085
2088
6
Qureshi
ST
LariviËre
L
Leveque
G
et al. 
Endotoxin-tolerant mice have mutations in Toll-like receptor4 (Tlr4).
J Exp Med.
189
1999
615
625
7
Glauser
MP
Zanetti
G
Baumgartner
J-D
Cohen
J
Septic shock: pathogenesis.
Lancet.
338
1991
732
736
8
Ulevitch
RJ
Tobias
PS
Receptor-dependent mechanisms of cell stimulation by bacterial endotoxin.
Annu Rev Immunol.
13
1995
437
457
9
Karima
R
Matsumoto
S
Higashi
H
Matsushima
K
The molecular pathogenesis of endotoxic shock and organ failure.
Mol Med Today.
March
1999
123
132
10
Scott
MRD
Westphal
K-H
Rigby
PWJ
Activation of mouse genes in transformed cells.
Cell.
34
1983
557
567
11
Liang
P
Pardee
AB
Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction.
Science.
257
1992
967
971
12
Velculescu
VE
Zhang
L
Vogelstein
B
Kinzler
KW
Serial analysis of gene expression.
Science.
270
1995
484
487
13
Velculescu
VE
Zhang
L
Zhou
W
et al. 
Characterization of the yeast transcriptome.
Cell.
88
1997
243
251
14
Zhan
L
Zhou
W
Velculescu
VE
et al. 
Gene expression profiles in normal and cancer cells.
Science.
276
1997
1268
1272
15
Polyak
K
Xia
Y
Zweier
JL
Kinzler
KW
Vogelstein
B
A model for p53-induced apoptosis.
Nature.
389
1997
300
305
16
Madden
SL
Galella
EA
Zhu
J
Bertelsen
AH
Beaudry
GA
SAGE transcript profiles for p53-dependent growth regulation.
Oncogene.
15
1997
1079
1085
17
Chen
H
Centola
M
Altschul
SF
Metzger
H
Characterization of gene expression in resting and activated mast cells.
J Exp Med.
188
1998
1657
1668
18
Hibi
K
Liu
Q
Beaudry
GA
et al. 
Serial analysis of gene expression in non-small cell lung cancer.
Cancer Res.
58
1998
5690
5694
19
Hashimoto
S-I
Suzuki
T
Dong
H-Y
Yamazaki
N
Matsushima
K
Serial analysis of gene expression in human monocytes and macrophages.
Blood.
94
1999
837
844
20
Hashimoto
S-I
Suzuki
T
Dong
H-Y
Nagai
S
Yamazaki
N
Matsushima
K
Serial analysis of gene expression in human monocyte-derived dendritic cells.
Blood.
94
1999
845
852
21
Fuhlbrigge
RC
Chaplin
DD
Kiely
J-M
Unanue
ER
Regulation of interleukin-1 gene expression by adherence and lipopolysaccharide.
J Immunol.
138
1987
3799
3802
22
Haskill
S
Johnson
C
Eierman
D
Becker
S
Warren
K
Adherence induces selective mRNA expression of monocyte mediators and proto-oncogenes.
J Immunol.
140
1988
1690
1694
23
Rollins
BJ
Chemokines.
Blood.
90
1997
909
928
24
Baggiolini
M
Chemokines and leukocyte traffic.
Nature.
392
1998
565
568
25
Polverini
PJ
Cotran
RS
Gimbrone
MA
Unanue
ER
Activated macrophages induce vascular proliferation.
Nature.
269
1977
804
806
26
Arras
M
Ito
WD
Scholz
D
Winkler
B
Schaper
J
Schaper
W
Monocyte activation in angiogenesis and collateral growth in the rabbit hindlimb.
J Clin Invest.
101
1998
40
50
27
Fràter-Schröder
M
Risau
W
Hallmann
R
Gautschi
P
Bohlen
P
Tumor necrosis factor type alpha, a potent inhibitor of endothelial cell growth in vitro, is angiogenic in vivo.
Proc Natl Acad Sci U S A.
84
1987
5277
5281
28
Leibovich
SJ
Polverini
PJ
Shepard
HM
Wiseman
DM
Shively
V
Nuseir
N
Macrophage-induced angiogenesis is mediated by tumor necrosis factor-alpha.
Nature.
329
1987
630
632
29
Wahl
SM
Wong
H
McCartney-Francis
N
Role of growth factors in inflammation and repair.
J Cell Biochem.
40
1989
193
199
30
Alderson
MR
Tough
TW
Ziegler
SF
Grabstein
KH
Interleukin-7 induces cytokine secretion and tumoricidal activity by human peripheral blood monocytes.
J Exp Med.
173
1991
923
930
31
Ziegler
SF
Tough
TW
Franklin
TL
Armitage
RJ
Alderson
MR
Induction of macrophage inflammatory protein-1 beta gene expression in human monocytes by lipopolysaccharide and IL-7.
J Immunol.
147
1991
2234
2239
32
Standiford
TJ
Strieter
RM
Allen
RM
Burdick
MD
Kunkel
SL
IL-7 up-regulates the expression of IL-8 from resting and stimulated human blood monocytes.
J Immunol.
149
1992
2035
2039
33
Webb
AC
Collins
KL
Snyder
SE
et al. 
Human monocyte Arg-Serpin cDNA. Sequence, chromosomal assignment, and homology to plasminogen activator-inhibitor.
J Exp Med.
166
1987
77
94
34
Potempa
J
Korzus
E
Travis
J
The serpin superfamily of proteinase inhibitors: structure, function, and regulation.
J Biol Chem.
269
1994
15957
15960
35
Wilhelm
SM
Collier
IE
Marmer
BL
Eisen
AZ
Grant
GA
Goldberg
GI
SV40-transformed human lung fibroblasts secrete a 92-kDa type IV collagenase which is identical to that secreted by normal human macrophages.
J Biol Chem.
264
1989
17213
17221
36
Welgus
HG
Campbell
EJ
Cury
JD
et al. 
Neutral metalloproteinases produced by human mononuclear phagocytes.
J Clin Invest.
86
1990
1496
1502
37
Matrisian
LM
Metalloproteinases and their inhibitors in matrix remodeling.
Trends Genet.
6
1990
121
125
38
Hla
T
Neilson
K
Human cyclooxygenase-2 cDNA.
Proc Natl Acad Sci U S A.
89
1992
7384
7388
39
Fukushi
M
Dixon
J
Kimura
T
Tsurutani
N
Dixon
MJ
Yamamoto
N
Identification and cloning of a novel cellular protein Naf1, Nef-associated factor 1, that increases cell surface CD4 expression.
FEBS Lett.
442
1999
83
88
40
Olah
ME
Stiles
GL
Adenosine receptor subtypes: characterization and therapeutic regulation.
Annu Rev Pharmacol Toxicol.
35
1995
581
606
41
Bouma
MG
Stad
RK
van den Wildenberg
FAJM
Buurman
WA
Differential regulatory effects of adenosine on cytokine release by activated human monocytes.
J Immunol.
153
1994
4159
4168
42
Merten
MD
Kammouni
W
Figarella
C
Evidence for, and characterization of, a lipopolysaccharide-inducible adenosine A2 receptor in human tracheal gland serous cells.
FEBS Lett.
369
1995
202
206
43
Kozopas
KM
Yang
T
Buchan
HL
Zhou
P
Craig
RW
MCL1, a gene expressed in programmed myeloid cell differentiation, has sequence similarity to BCL2.
Proc Natl Acad Sci U S A.
90
1993
3516
3520
44
Zhou
P
Qian
L
Bieszczad
CK
et al. 
Mcl-1 in transgenic mice promotes survival in a spectrum of hematopoietic cell types and immortalization in the myeloid lineage.
Blood.
92
1998
3226
3239
45
Worthington
MT
Amann
BT
Nathans
D
Berg
JM
Metal binding properties and secondary structure of the zinc-binding domain of Nup475.
Proc Natl Acad Sci U S A.
93
1996
13754
13759

Author notes

Kouji Matsushima, Department of Molecular Preventive Medicine, School of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; e-mail:koujim@m.u-tokyo.ac.jp.