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PHAGOCYTES
From the Department of Genetics, Boyer Center for
Molecular Medicine, Yale University School of Medicine, and the
Department of Molecular Biophysics and Biochemistry, Yale University,
New Haven, CT; and the Departments of Molecular Genetics/Microbiology
and Pediatrics, University of Massachusetts Medical School, Worcester.
A comprehensive study of changes in messenger RNA (mRNA)
levels in human neutrophils following exposure to bacteria is
described. Within 2 hours there are dramatic changes in the levels of
several hundred mRNAs including those for a variety of cytokines,
receptors, apoptosis-regulating products, and membrane trafficking
regulators. In addition, there are a large number of
up-regulated mRNAs that appear to represent a common core of activation
response genes that have been identified as early-response products to
a variety of stimuli in a number of other cell types. The activation
response of neutrophils to nonpathogenic bacteria is greatly altered by exposure to Yersinia pestis, which may be a major factor
contributing to the virulence and rapid progression of plague. Several
gene clusters were created based on the patterns of gene induction caused by different bacteria. These clusters were consistent with those
found by a principal components analysis. A number of the changes could
be interpreted in terms of neutrophil physiology and the known
functions of the genes. These findings indicate that active regulation
of gene expression plays a major role in the neutrophil contribution to
the cellular inflammatory response. Interruption of these changes by
pathogens, such as Y pestis, could be responsible, at least
in part, for the failure to contain infections by highly virulent organisms.
(Blood. 2001;97:2457-2468) Neutrophils are the first cells to be recruited from
the blood stream to sites of inflammation1,2 and are
critically important for determining the outcome of some acute
infections.3 They are postmitotic cells that synthesize
lower levels of protein and RNA than most dividing cells, and they can
interact and/or modulate inflammation. Nevertheless, on exposure to
bacteria or other activating agents, neutrophils are known to
synthesize and secrete a number of cytokines4,5 including
interleukin-1 (IL-1),6 IL-8,7,8 oncostatin
M,9 and small inducible cytokine A3/macrophage
inflammatory protein 1 Neutrophils are readily isolated from human peripheral blood. The
isolated cells are more than 99% pure, with the principal contaminant
being eosinophils, which themselves have relatively low levels of
macromolecular synthetic activity. The cells can be synchronously
exposed to "natural" stimuli such as opsonized bacteria and offer
an attractive system for the study of gene expression in terminally
differentiated cells. Although the cell biology of neutrophil
activation has been studied in some detail, studies of responses at the
messenger RNA (mRNA) level have been circumscribed, focusing
principally on one or a few cytokine mRNA species.
Approaches for simultaneously detecting changes in levels of many of
the polyadenylated RNA in a cell population fall into 3 categories:
hybridization to arrays of targets complementary to specific mRNAs,
sequencing of many randomly chosen complementary DNA (cDNA) fragments,
or display of specific cDNA fragments on gels. A method for display of
3'-end restriction fragments of each species of RNA13 has
the advantages that the position of fragments corresponding to known
genes is predictable and that no prior knowledge of the sequence is
needed to detect previously "unknown" genes.
We have applied cDNA display to study changes in mRNA levels in
neutrophils activated by exposure to various bacteria. Sufficient analyses were performed to detect, on a statistical basis, more than
90% of all changes in transcripts. We used time-course studies to get
insight into the mechanisms underlying these changes. There is a
dramatic and complex change in the gene expression profiles of
activated neutrophils, indicating an important role for neutrophil gene
regulation in the propagation and early evolution of the inflammatory response.
Bacterial strains and culture
Overnight cultures of Y pestis grown in modified
Tryptose Blood Agar Base without the agar comprising 10 g
tryptose, 3 g beef extract, and 5 g sodium chloride (NaCl)
per liter supplemented with 2.5 mM calcium dichloride
(CaCl2) were diluted to a density of 3 × 107
bacteria per mL and incubated for 3 hours at 26°C in a water bath. At
this point the temperature was shifted to 37°C, and the incubation
was continued for an additional 2 hours. The bacteria were collected by
centrifugation, washed with Hanks balanced salt solution (HBSS; without
Ca++ or Mg++), resuspended in HBSS to a
final density of 1.75 × 109 bacteria per mL and opsonized
by the addition of 1.5 volumes of normal human serum incubated at
37°C for 20 minutes, washed twice with RPMI 1640 supplemented with
10% heat-inactivated fetal calf serum (FCS), and resuspended to a
final density of 7 × 108 bacteria per mL.
Overnight cultures of E coli K12 grown in LB were diluted
1:100 and incubated for 2 hours at 37°C. They were then washed and opsonized as described above, except that C7-deficient human serum (Sigma Chemical, St Louis, MO) was used. This precaution was not necessary with Y pestis, which is completely resistant to
complement-mediated lysis.
Cell separation and activation by bacteria
Freshly isolated neutrophils and opsonized bacteria, suspended in RPMI plus 10% heat-inactivated FCS, were mixed to final densities of 2 × 106 cells per mL and 4 × 107 bacteria per mL, respectively. These cultures or control neutrophils were then incubated for 2 hours, or other indicated times, at 37°C with gentle agitation. Monocytes were isolated from the peripheral blood mononuclear cells by a spontaneous aggregation method at 4°C.22 To activate monocytes, they were exposed for 2 hours to opsonized E coli K12 at a ratio of 20 bacteria per cell, which is the same procedure that was used for activation of neutrophils. Time-course experiments were analyzed with neutrophils incubated for at least 3 time points including 0 minutes (negative control), 10-30 minutes (early), and 120 minutes (late) with E coli K12 . Northern blot analysis and in situ hybridization Northern blot analysis of total cell RNA, extracted from neutrophils by the guanidine hydrochloride (HCl) method,21,23 was performed as described.24-26 Levels of hybridization were measured quantitatively by the Phosphorimager System (Molecular Dynamics, Sunnyvale, CA) and normalized to the 18S ribosomal RNA signals. In situ hybridization was performed by a previously described method,27 using Cy3 and FluorX (Amersham Pharmacia Biotech, Piscataway, NJ) labeled oligonucleotide probes.Gel display of 3'-end restriction fragments cDNA displays of cells activated by bacteria were prepared as previously described in detail.21,28 Bands were displayed on sequencing gels run to display products of at least 100 bases in length. Bands were excised, amplified by polymerase chain reaction (PCR), and sequenced. The enzymes used to digest cDNA for comparison of the effects of Y pestis with those of E coli were BamHI, BclI, BglII, BsrGI, ClaI, EagI, EcoRI, HindIII, NcoI, PstI, and XbaI. Enzymes used for time-course studies were ApaI, BglII, HindIII, KpnI, SacI, SpeI, SphI, and XbaI.For most experiments, every band that differed in relative intensity between the control pattern and any of the experimental patterns was sequenced. In different experiments using the same restriction enzymes, many bands could be confidently recognized as corresponding to previously sequenced bands on the basis of both band pattern and sequence. Informatics Most of the band intensities were quantified by eye, confirmed by a second investigator, and expressed as a single-digit numeric. A part of the bands was quantified by using the Phosphorimager. The integrated density of each band above background was calculated as a "volume" by the Phosphorimager, as described in Figure 1. A least-square linear regression model of the logarithm of the "volume" (
 is X averaged, and
 
confidence interval (CI) for
2,) is the
2-tailed t-value of a t-distribution with n 2 degrees of
freedom.
The accuracy of such confidence limits depends on the validity of the
assumption of linearity and equally normal distributions of
Y values across all values of X. However,
measurements by the Phosphorimager at very low intensities are
much less reliable. Therefore we fit the data to a linear regression
model based on measurements at X > 1, yielding
Quantitative measurement of Northern blots of several mRNAs confirms
that genes identified by gel display to be up- or down-regulated do
indeed show increases or decreases of mRNA levels. These changes range
from a 10-fold decrease to a 71-fold increase (Table
1), and the logarithm of the values
correlate to estimates from the gel display method (Pearson correlation
r = 0.92).
Each sequence was searched against nr and dbest databases of the National Center for Biotechnology Information (NCBI) by the Basic Local Alignment Search Tool (BLAST) program (http://www.ncbi.nlm.nih.gov/BLAST/blast_overview.html).29 Matches to known genes were confirmed to come from the 3'-untranslated regions of mRNA except where otherwise noted. The length of sequence obtained was compared with the size of bands on the display gel as a quality check. A database was created by Shigeru Yamaga, jointly with Wen Ming Xiao (Gene Logic, Gaithersburg, MD), using Microsoft Access (Microsoft, Redmond, WA) as a database engine. An individual record was created for every differentially expressed band, and related information was entered as hypertext links to sequence files, search results of GenBank and TIGR databases, bands of overlapping sequence, references to relevant literature, keys for various classifications of bands, presence of polyA signals, quality of sequence, and scanned gel images, etc. We used LocusLink ID,65 when available, as a unique key to known genes, and we used the terms listed as gene symbol (the HGMW-approved symbol, where applicable) and gene name. For ESTs, we used UniGene cluster numbers as a unique key.66 Subsequently all sequences were clustered by a modified PHRAP approach.30 Public gene database search was completed on November 9, 2000.
Quality of cell and RNA preparation Morphologically, our neutrophil preparations were more than 99% pure except for the presence of 1% to 3% eosinophils; band forms accounted for less than 3% of the cells. No cells with the typical morphology of monocytes could be identified by light microscopy, nor did flow cytometry reveal any monocytes. Occasional preparations with more than 0.5% monocytes were discarded. The yield of total RNA from the neutrophil preparations averaged 13 µg/108 cells (range, 7-17 g/108 cells). We examined the distribution of IL-8 transcripts by in situ hybridization using a combination of 2 CY-3 (red)-labeled oligonucleotides complementary to different regions of the mRNA. IL-8 transcripts were detectable in virtually all neutrophils after incubation for 2 hours with E coli, although the intensity of RNA staining was somewhat variable from cell to cell. Neutrophils incubated in the absence of bacteria showed considerably less intense staining (data not shown).We prepared monocytes and neutrophils from the same blood sample.
Both types of cells were exposed to E coli K12 for 2 hours and then harvested for cDNA display (Table
2 and Figure
2, left). In some cases RNA species that
were among the most strongly induced in neutrophils were actually
down-regulated in monocytes, excluding the possibility that monocytes
activated by the bacteria were contributing to the observed pattern for
these species. Northern blots also showed that RNA extracted from the
neutrophils did not contain detectable transcripts for
c-fms,31 the receptor for macrophage
colony-stimulating factor (MCSF) (data not shown).
Changes in gene expression profile in neutrophils exposed to bacteria We undertook an extensive comparison of the cDNAs generated from control neutrophils and neutrophils treated for 2 hours with one of 3 bacteria: E coli K12, Y pestis strain KIM5, or Y pestis strain KIM6. A total of 17 different restriction enzymes were used for these displays, and fragments from each enzyme digest were displayed with each of the 12 possible 3'-terminal dinucleotides on the oligo-dT primer. On average, approximately 100 bands per lane could be evaluated visually. In most cases we analyzed the sequences of all bands whose inserts were in the size range of 75-600 base pairs (bp) and whose intensities differed by more than 2-fold between control and treated samples. Bands up to greater than 1 kb in length were analyzed if they were prominent and showed clear differences between samples. Based on the number of bands observed and on the frequency of randomly distributed restriction sites, we should have achieved an average of 1.5 representations of mRNA of intermediate abundance, with a higher frequency for the abundant mRNAs.Striking differences were evident in patterns of cDNA display between
control neutrophils and neutrophils exposed to bacteria (Figure 2,
right). A total of 1887 bands were sequenced (Table 3). Of these, approximately 19% did not
give good sequence. A portion of these sequences still gave high
probability matches to known sequences so that the bands could be
identified. Any single prominent band is unlikely to represent more
than a few percent of total mRNAs. This implies that bands
corresponding to one mRNA molecule per cell are visible, except where
obscured by darker bands. Redundancy in analyses occasionally occurred, particularly for some of the most prominent RNAs. Multiple bands representing the same transcript could arise by buckling out of nucleotides during oligo-dT priming, but often resulted from alternate sites of polyA addition in mRNAs.
In total, 350 known genes and 292 EST or anonymous sequences were found to change substantially in expression level by 2 hours after activation with bacteria. The anonymous cDNA could be derived from unrecognized alternate polyadenylation sites in genes represented elsewhere in the database, cDNA primed from A-rich internal sequences in mRNA or heterogeneous nuclear RNA, or genes not yet represented in the EST databases or GenBank. Five of the bands represented perfect copies of EST sequences derived from repetitive sequences. The perfect match in these cases suggests that the genomic template has been identified. We obtained 48 nonrepetitive sequences that had no match in the gene databases. About half of these had a perfect polyA signal or a hexanucleotide that differed by a single base from the consensus AAUAAA sequence.32 Such deviation is commonly seen in mRNAs for known genes, so it is likely a large fraction of these represent polyadenylated RNA. Approximately 8% of the sequences corresponded to repetitive sequence, and most of them did not precisely match anything in the database. These frequently lacked even an approximate polyA addition signal. However, 4 different specific repetitive sequences were strongly induced in the neutrophils by exposure to bacteria. Increased transcription of repetitive sequences has been noted in stimulated cells and may have a physiologic role.33 Clustering neutrophil gene expression patterns We grouped the neutrophil genes according to their expression profiles under 4 conditions in the following order: control, incubation with E coli K12 for 2 hours, and incubation with KIM5 (pCD1+) and KIM6 (pCD1) strains of Y pestis. We clustered
the genes according to their similarity to idealized expression
patterns. For instance, the expression pattern of an ideal gene that is overexpressed (high) for the virulent KIM5 condition and
under-expressed (low) for the control, E coli K12, and
avirulent KIM6 conditions would be low-low-high-low (described as
"LLHL"). Overall we have 24 2 idealized patterns
excluding HHHH and LLLL. The Pearson correlation was used as the
measure of similarity of each gene expression pattern,
x = (x1,x2,x3,x4)
to each of the 14 idealized patterns y = (y1,y2,y3,y4).
The order of the entries for each gene expression vector x
or y is control, E coli, KIM5, and then KIM6. The
query gene is assigned to a cluster designated by the idealized pattern that has the maximal correlation with that gene. Figure
3 shows 2 representative normalized gene
expression patterns of neutrophils, LHLH (upper) and HLHL
(lower).
To show the affinity between genes classified to the same cluster,
principal components analysis (PCA) was performed. Genes tend to
coalesce in homogeneous clusters determined by their similarity to an
ideal expression pattern (Figure 4).
Thus, our criterion for classifying genes according to their similarity
to predetermined idealized expression patterns allows us to recognize
well-separated clusters. We note that this is equivalent to the first
iteration of the standard k-means clustering technique.34
There are 2 differences from k-means: (1) our clustering
method does not require reassignment of new centers for all clusters,
as is done at each k-means iteration step, and (2) the centers are
predetermined by the idealized expression profiles as opposed to a
random centers' initialization, which is the first step of the k-means
algorithm.
Genes differently expressed in neutrophils exposed to Y pestis We also compared the effects of 2 strains of Y pestis, the causative agent of plague, on neutrophils. The high virulence of this pathogen is in part due to its ability to prevent the accumulation of neutrophils at foci of infection early in the course of disease.15,35,36 An important contribution of the type III secretion system to suppressing neutrophil accumulation is the inhibition of cytokine production.37,38The most common pattern of mRNA change was a substantial increase in
response to E coli or KIM6, but there was no change in response to KIM5 (Table 4, LHLH). Most of
the cytokines we identified showed this pattern. A second common
pattern is that mRNAs present in the control and KIM5-treated cells
were depressed in the cells treated with E coli and KIM6
(Table 4, HLHL). This pattern also confirms that most of the cells
received a stimulus as a result of exposure to the bacteria. A smaller
number of mRNAs were induced or substantially up-regulated only by
KIM5 (Table 4, LLHL). Overall the effects of nonpathogens on genes
listed in Table 4 were quite parallel, presumably because the bacteria
present common stimuli.
The expression of a smaller number of mRNAs appeared to be influenced
by Y pestis, regardless of pCD1 but not by E coli
(Table 5, LLHH and HHLL). Some genes were affected only by
E coli (LHLL and HLHH), and a number were regulated alike by
all 3 bacteria (LHHH and HLLL). Many of the changes in the levels of
mRNA could be interpreted in terms of the known behavior of
neutrophils. Activation of neutrophils by the nonpathogenic
gram-negative bacteria induced expression of a variety of cytokines and
receptors. Several known cytokines have not been previously associated
with neutrophils or were first described in this context after the
present analyses were completed. These include SCYA20 (LARC/MIP3A),
oncostatin M, GRO1, and GRO2.
Putative membrane trafficking regulators were up-regulated in a functionally coordinate fashion. Thus mRNAs encoding the 3 small guanosine 5'-triphosphatases (GTPases), RAB1, RAB5A, and RAB7, were all up-regulated by E coli and KIM6. Interestingly, KIM5 slightly up-regulated RAB1 and RAB5A, but strongly up-regulated RAB7, a small GTPase implicated in transport from late endosomes to lysosomes. ARHGDIB, a guanine nucleotide dissociation inhibitor that would presumably delay reconversion of the GDP-bound form to the active GTP-bound form of these proteins, was down-regulated by nonpathogens, while KIM5 did not change its expression (Table 4, HLHL). Apoptosis of neutrophils in vitro is delayed by various activating stimuli. Examination of the RNAs up-regulated by the nonpathogens offers several potential mechanisms for this effect. BCL2A1 was strongly induced, as previously reported for activated monocytes.39 BCL2A1 has antiapoptotic properties, but unlike BCL2, it does not inhibit the accumulation of differentiated myeloid cells from the 32D cell line.40 MCL1 is another strongly up-regulated product implicated as an antiapoptotic protein. IER3 is a p53 responsive gene that protects cells from FAS- or TNF-induced apoptosis.41 One of the most strongly up-regulated mRNAs was that for PPIF (cyclophilin F). This protein is a mitochondrial peptidyl-prolyl isomerase implicated in mitochondrial pore structure and perhaps permeability transitions.42 This is intriguing because cytochrome c release from mitochondria is a component of a caspase-activating system central to many forms of apoptosis. The mRNA encoding certain subunits of the vacuolar adenosine 5'-triphosphate (ATP)-dependent H+ pump, another potential downstream antiapoptotic factor, were also up-regulated. KIM5 had little effect on most of the above genes. Changes in neutrophil gene expression were asynchronous The changes in mRNA expression patterns at short time intervals following the addition of E coli K12 were also analyzed. Many of the striking increases in mRNA levels seen at 2 hours after exposure to bacteria were not reflected by changes in levels of the corresponding mRNA within the first 60 minutes, although the levels of some mRNAs progressively increased beginning within 30 minutes (Table 6, LHL and LHH). Display of BglII-cut cDNAs prepared 3 and 4 hours after exposure to E coli showed a pattern that was for the most part similar to the 2-hour pattern (data not shown).
Some genes were transiently up-regulated, peaking at 30-60 minutes, but returning to baseline levels by 2 hours after treatment. Among the earliest response mRNAs for known genes was that for the dual-specificity protein kinase DYRK1A.43,44 This is the human homolog of Drosophila minibrain and potentially a homolog of the S cerevisiae gene YAK1, a possible negative regulator of growth and cell cycle progression.45 By 60 minutes after activation, the pattern changed with down-regulation of some mRNAs and strong up-regulation of others, among which was the mRNA for ETR101,46 a proline-rich cytoplasmic protein known as a sometimes unstable early activation protein in other systems.
The current study demonstrates that neutrophils are capable of extensive, rapid, and complex changes in gene expression. The changes in mRNA levels include both genes that are expressed and regulated in many cell types and genes that are expressed in a limited range of cells. Few of the regulated genes were strictly neutrophil-specific. Activation of neutrophils by bacteria is a complex process that delivers multiple types of exogenous and endogenous signals to the cell. The bacterial lipopolysaccharide itself interacts with a specific receptor on the cell surface, and bacterially derived formyl peptides interact with the FMLP receptor (FPR1). Immunoglobulins and complement components associated with the bacteria stimulate an array of receptors present on neutrophils. An early consequence of neutrophil activation is the production of reactive oxygen species, and these in turn elicit a stress response from the cells. Neutrophil production of IL-1 or granulocyte-macrophage colony-stimulating factor (GM-CSF) presumably activates the corresponding receptors on the cell surface. The relative kinetics of induction of IL-8 and down-regulation of its receptors offer another potential for feedback effects on neutrophil activation. In our study many known genes were induced on neutrophil activation including G0S2, ZFP36 (TTP/G0S24), PBEF (G0S9), ETR101, COPEB, FOSB (G0S3), FOS (G0S7), and the urokinase receptor (PLAUR). These corresponded to mRNA appearing in many other cell types during the transition from G0- to S-phase of the cell cycle or after other modes of activation. Other genes for widely used stress-response proteins, such as the heat shock products (HSPA10, HSPCA, HSPCB, and HSPF1) and the protein kinase MAP2K3, were also activated. Two groups recently reported array analysis of changes in gene expression in fibroblasts in response to PDGF receptor47 or serum48 stimulation. For cells induced by receptor stimulation, more than 40% of the genes induced within 4 hours of stimulation were induced in neutrophils by 2 hours. This is an impressive overlap, as the fibroblasts were a transformed murine cell line held in 0.5% serum, whereas the neutrophils are postmitotic normal human cells maintained in high serum. This overlap emphasizes a commonality of very early response transcripts in mammalian cells, but suggests that quantitative considerations of the time and level of mRNA production may be central to understanding the differences in behavior of cell types. None of the signal transduction or cell cycle genes induced in fibroblasts47 was regulated in neutrophils. However, more than 40% of immediate-early transcription factors were also up-regulated in neutrophils, and 7 of 8 genes classified as inflammation-related were also up-regulated in neutrophils. Itoh et al49 analyzed the 3'-end sequences of 1142 cDNA clones from neutrophils that were not intentionally activated and obtained sequences for 748 independent species. They listed 46 named genes for which they recovered 3 or more clones. In the present study we found that 90% of these genes were up-regulated on neutrophil activation. Our data indicate that activated neutrophils are a source of physiologically significant trans-cellular signaling molecules. Measurements of IL-8 protein accumulation have shown that neutrophils produce IL-8 at about 1 ng per million cells per hour after exposure to E coli (J.D.G. and Y.V.B.K.S., unpublished results, February 1994). This corresponds to approximately 105 molecules of IL-8 per cell per hour. In vitro, the cellular activating effects of IL-8 reach half-saturation levels at a concentration range of 0.5-1.0 nM. In vivo, human neutrophil counts commonly rise above 10 million cells per mL blood, enough to raise the concentration of IL-8 to physiologically effective levels within 1-2 hours. At sites of infection, tissue neutrophils are considerably more concentrated. Therefore, the levels of IL-8 production by neutrophils are physiologically very significant. The levels of induced mRNA for a number of intracellular proteins are
comparable to those for the more abundant cytokine mRNAs. This
strongly suggests that the intracellular molecules are produced at
levels that are physiologically significant, although the possibility of concomitant negative control of translation rate of specific mRNAs
has not been investigated. More caution is necessary in interpretation
of down-regulation of mRNA. The down-regulation will only correspond to
changes in protein level if the protein normally has a short half-life
or is specifically degraded following activation of the neutrophils.
Some of the down-regulation is undoubtedly due to stopping
transcription of relatively short-lived mRNAs. This change would not
produce synchronous effects on all mRNA both because they have
differing half-lives and because transcription may not be
down-regulated simultaneously on different genes. Some mRNAs that are
stable in cells treated with
5,6-dichloro-1- CC-chemokines, such as SCYA3, SCYA4, and SCYA20, were up-regulated. CXC chemokines, such as IL-8, GRO1, and GRO2, were also up-regulated. Although GRO1 and GRO2 share 90% identity at the deduced amino acid level, and both have melanoma growth-stimulating activity, their expression patterns were different. GRO1 was induced by KIM5 more strongly than by nonpathogenic bacteria, but the induction of GRO2 seen with KIM6 did not occur with KIM5. Although both CXCR1 (IL-8RA, a receptor that is relatively specific for IL-8) and CXCR251 (IL-8RB, a receptor activated by other CXC chemokines including GRO1) were down-regulated, KIM5 fully inhibited gene expression of CXCR1, but not CXCR2. CXCR1 and CXCR2 are regulated in different modes by CXC chemokines and play diverse roles in mediating the inflammatory process.52 The putative G protein-coupled receptors CCRL2 (HCR) and HM74 were prominently up-regulated. HCR was previously identified in public databases as CCR6 (a receptor for SCYA20/LARC/MIP3A), but recently it has been described as a distinctive receptor, CCRL2. The sequence of CCRL2 in GenBank Accession no. U95626 is identified as CCR6, but differs from the sequence of U68030 CCR6 mRNA, so it remains uncertain whether CCRL2 is the receptor of SCYA20/LARC/MIP3A. The presence of both SCYA20/LARC/MIP3A and its receptor on the same cells would imply an autocrine loop. The strong induction of HM74 in human neutrophils suggests its utility as a clinical parameter and/or a drug target in inflammatory disorders. Overall, the responses to some stimuli were down-regulated, and new response pathways could be established. Whether these maintain or modulate the active state or have other functions remain to be determined, but they probably play important roles in the early evolution of the inflammatory process. A suggestion to explain the virulence of KIM5 is that the loss of production of the primary activating and chemo-attractant cytokine IL-8 would decrease the possibility that neutrophils which have ingested bacteria would attract additional neutrophils to sites of inflammation. The net effects of up-regulation of IL-1 and its receptor antagonist IL-1RN are uncertain, but they could provide an additional measure of feedback. The balance between apoptotic and necrotic cell death in neutrophils plays an important role in the control of inflammation. Neutrophils accumulate in large numbers at sites of inflammation, forming tissue infiltrates and pus. Necrotic death of these cells releases toxic granule contents, such as elastase and collagenase, whereas removal of apoptotic neutrophils by macrophages protects surrounding tissues from such damage.53,54 However, inhibition of neutrophil apoptosis may augment host defense against infection by prolongation of functional longevity of the cells.55 When cultured in vitro, neutrophils rapidly undergo apoptosis, which is preceded by intracellular acidification.56 G-CSF and a variety of inflammatory mediators delay programmed cell death, in part by up-regulation of expression of Bcl-X1, but not other Bcl-2 family members.53,56-58 The current data suggest that other proteins, such as BCL2A1, MCL1, PPIF, TNFAIP3, and perhaps spermidine/spermine N1-acetyltransferase (SAT), may be important for the regulation of neutrophil apoptosis in response to infection. Increases in mRNA for genes regulating transcription or translation were observed 2 hours after activation. These include the COPEB gene, which is reported to stimulate expression of genes lacking a TATA box. In cells exposed to KIM5, 12 of 14 transcription-modifying genes examined were present at levels more similar to those of control neutrophils than of the neutrophils stimulated by the other bacteria. In time-course studies we found that NFKBIA (I Activation by nonpathogens, but not by the pathogenic KIM5, caused down-regulation of mRNAs for some antibacterial products, including the phagocyte oxidase (PHOX) system (NCF1, NCF2, and NCF4) generating reactive oxygens,60 and the calgranulins (S100A8 and S100A9). In contrast, the free radical scavenging enzyme SOD2 was up-regulated by the nonpathogens. The reactive oxygen system is regulated by external stimuli61 and is auto-cytotoxic for neutrophils. Its down-regulation may contribute to the prolongation of life span of activated cells in inflammation. Decay-accelerating factor (DAF) was up-regulated by nonpathogen, but MCP,62 a cofactor of serine protease factor I for inactivation of complements C3b and C4b, was down-regulated. Although both play a protective role in host cells against homologous complement, MCP is also the receptor for various viruses and bacterial pathogens. CD97,63 the receptor for DAF, is regulated oppositely to DAF, so that the cells may become desensitized to DAF. Overall, the patterns of induction or disappearance of mRNAs for genes of known function can largely be rationalized in terms of the biologic role of neutrophils. Several different antiapoptotic mechanisms are set in play in an asynchronous fashion. This response would allow neutrophils that ingested nonpathogenic material to survive longer, potentially migrating to restricted tissue areas and also degrading ingested material. Additional defensive changes in the neutrophils include production of DAF. The cells change their own cytokine responsiveness and begin producing a range of new cytokines. These would not only transmit inflammatory signals and recruit unstimulated neutrophils, but they would also further stimulate activated neutrophils, contributing to the congregation of activated neutrophils and hence to abscess formation. Changes in the levels of intracellular signaling molecules might well change the responses to stimulation of pre-existing receptors. Membrane trafficking is accelerated perhaps related to ingestion of bacteria and discharge of preformed granules. There is also a previously unappreciated transition from early to delayed responses at the level of mRNA production. In summary, nonpathogenic gram-negative bacteria induce a marked change in the patterns of gene expression in neutrophils, indicating massive changes in cytokine output and prolongation of cell survival. These changes imply that neutrophils are important effectors of the progression of the cellular inflammatory response. Interruption of these changes by pathogens, such as Y pestis KIM5, could be, at least in part, responsible for the failure to contain the infectious process. Supplementary information is available on our Web site.67
We thank Andrea M. Neuman, Carolyn Padden, Angela Plette, Anne-Marie Quinn, and Connie Whitney for technical assistance and Dov Greenbaum for Web site set-up.
Y.V.B.K.S. and S.Y. contributed equally to this work.
Submitted August 1, 2000; accepted November 30, 2000.
Supported by grants AI22176 (J.D.G.), CA42556 (S.M.W.), and DK54369 (P.E.N.) from the National Institutes of Health, Bethesda, MD, and by a research grant (P.E.N.) from the Arthritis Foundation.
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.
Reprints: Sherman M. Weissman, Department of Genetics, Boyer Center for Molecular Medicine, Yale University School of Medicine, 295 Congress Ave, New Haven, CT 06536-0812; e-mail: sherman.weissman{at}yale.edu.
1. Newburger PE, Parmley RT. Neutrophil structure and function. In: Hoffman R,Benz EJ Jr,Shattil SJ,Furie B,Cohen HJ,Silberstein LE, eds. Hematology: Basic Principles and Practice. New York, NY: Churchill Livingstone; 1995:738-750.
2.
Ward PA, Lentsch AB.
The acute inflammatory response and its regulation.
Arch Surg.
1999;134:666-669 3. Wiseman H, Halliwell B. Damage to DNA by reactive oxygen and nitrogen species: role in inflammatory disease and progression to cancer. Biochem J. 1996;313:17-29. 4. Lindemann A, Riedel D, Oster W, Ziegler-Heitbrock HW, Mertelsmann R, Herrmann F. Granulocyte-macrophage colony-stimulating factor induces cytokine secretion by human polymorphonuclear leukocytes. J Clin Invest. 1989;83:1308-1312. 5. Cassatella MA, Gasperini S, Russo MP. Cytokine expression and release |
Top
Abstract
Introduction
lac-3350 galK2 galT22
(X0) · Tvalue(38,0.05) 
0.5.
-D-ribofuranosylbenzimidazole (DRB)
disappear rapidly after exposure to bacteria (data not shown). Studies
with actinomycin D indicate that the mRNA for certain chemokine
receptors is destabilized on LPS activation of cells,
B
) was
activated rather later. I