A distinct peripheral blood monocyte phenotype is associated with parasite inhibitory activity in acute uncomplicated Plasmodium falciparum malaria.

Abstract

Monocyte (MO) subpopulations display distinct phenotypes and functions which can drastically change during inflammatory states. We hypothesized that discrete MO subpopulations are induced during malaria infection and associated with anti-parasitic activity. We characterized the phenotype of blood MO from healthy malaria-exposed individuals and that of patients with acute uncomplicated malaria by flow cytometry. In addition, MO defense function was evaluated by an in vitro antibody dependent cellular inhibition (ADCI) assay. At the time of admission, the percentages and absolute numbers of CD16+ MO, and CCR2+CX3CR1+ MO, were high in a majority of patients. Remarkably, expression of CCR2 and CX3CR1 on the CD14(high (hi)) MO subset defined two subgroups of patients that also differed significantly in their functional ability to limit the parasite growth, through the ADCI mechanism. In the group of patients with the highest percentages and absolute numbers of CD14(hi)CCR2+CX3CR1+ MO and the highest mean levels of ADCI activity, blood parasitemias were lower (0.14+/-0.34%) than in the second group (1.30+/-3.34%; p = 0.0053). Data showed that, during a malaria attack, some patients' MO can exert a strong ADCI activity. These results bring new insight into the complex relationships between the phenotype and the functional activity of blood MO from patients and healthy malaria-exposed individuals and suggest discrete MO subpopulations are induced during malaria infection and are associated with anti-parasitic activity.

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A Distinct Peripheral Blood Monocyte Phenotype Is
Associated with Parasite Inhibitory Activity in Acute
Uncomplicated Plasmodium falciparum Malaria
Pattamawan Chimma1,2, Christian Roussilhon1, Panudda Sratongno2, Ronnatrai Ruangveerayuth3, Kovit
Pattanapanyasat2, Jean-Louis Pe ´rignon1, David J. Roberts4,5, Pierre Druilhe1*
1Bio-medical Parasitology Unit, Institut Pasteur, Paris, France, 2Center of Excellence for Flow Cytometry, Office for Research and Development, Faculty of Medicine, Siriraj
Hospital, Mahidol University, Bangkok, Thailand, 3Mae Sot Hospital, Mae Sot, Tak, Thailand, 4Nuffield Department of Clinical Laboratory Sciences, Oxford, United
Kingdom, 5National Blood Service Oxford Centre, John Radcliffe Hospital, Oxford, United Kingdom
Abstract
Monocyte (MO) subpopulations display distinct phenotypes and functions which can drastically change during
inflammatory states. We hypothesized that discrete MO subpopulations are induced during malaria infection and
associated with anti-parasitic activity. We characterized the phenotype of blood MO from healthy malaria-exposed
individuals and that of patients with acute uncomplicated malaria by flow cytometry. In addition, MO defense function was
evaluated by an in vitro antibody dependent cellular inhibition (ADCI) assay. At the time of admission, the percentages and
absolute numbers of CD16+MO, and CCR2+CX3CR1+MO, were high in a majority of patients. Remarkably, expression of
CCR2 and CX3CR1 on the CD14high (hi)MO subset defined two subgroups of patients that also differed significantly in their
functional ability to limit the parasite growth, through the ADCI mechanism. In the group of patients with the highest
percentages and absolute numbers of CD14hiCCR2+CX3CR1+MO and the highest mean levels of ADCI activity, blood
parasitemias were lower (0.1460.34%) than in the second group (1.3063.34%; p=0.0053). Data showed that, during a
malaria attack, some patients’ MO can exert a strong ADCI activity. These results bring new insight into the complex
relationships between the phenotype and the functional activity of blood MO from patients and healthy malaria-exposed
individuals and suggest discrete MO subpopulations are induced during malaria infection and are associated with anti-
parasitic activity.
Citation: Chimma P, Roussilhon C, Sratongno P, Ruangveerayuth R, Pattanapanyasat K, et al. (2009) A Distinct Peripheral Blood Monocyte Phenotype Is
Associated with Parasite Inhibitory Activity in Acute Uncomplicated Plasmodium falciparum Malaria. PLoS Pathog 5(10): e1000631. doi:10.1371/journal.
ppat.1000631
Editor: James W. Kazura, Case Western Reserve University, United States of America
Received May 11, 2009; Accepted September 24, 2009; Published October 23, 2009
Copyright: ? 2009 Chimma et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work is part of activities carried out in the BioMalPar program (European Grant number LSHP-CT-2004-503578) and was also supported by the
Thailand Research Fund - Senior Research Scholar. P.C. is supported by a BioMalPar PhD program and D.J.R. is supported by the National Blood Service and the
Howard Hughes Medical Institute. The research benefited from NHS R&D funding through the National Institute of Health Research (NIHR). The funders had no
role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: druilhe@pasteur.fr
Introduction
Innate defenses against malaria play a vital role in the clearance
of Plasmodium-infected red blood cells (iRBCs) in murine and
human infections [1–5]. This innate response against iRBCs is, at
least in part, related to the functional activity of monocytes (MO) -
macrophages and/or polymorphonuclear leukocytes. These my-
eloid cells can also modulate the inflammatory process and trigger
the adaptive immune responses. Circulating blood MO, not only
contribute directly to defense against Plasmodium parasites by their
phagocytic activity, but also achieve parasite killing through an
indirect mechanism known as antibody-dependant cellular
inhibition (ADCI) [6]. Moreover, MO also supply peripheral
tissues with macrophage and dendritic cell (DC) precursors.
The generic name ‘monocyte’ corresponds to a very large
number of distinct phenotypes representing a highly heteroge-
neous population of cells, which is reflected in the complex MO
response to falciparum malaria. The existence of distinct MO
populations in human blood was initially described by Ziegler-
Heitbrock and it is clearly established that subsets of MO can be
influenced by infection [7–9]. Human MO can be divided into 2
major subsets by the differential expression of lipopolysaccharide
(LPS) receptor (CD14) and the low affinity Fcc receptor III
(CD16). These two MO subsets vary in chemokine receptor,
adhesion molecule expression, migratory and differentiation
properties [9–11]. Up to 90–95% of the blood MO are CD14hi
CD162, they are usually known as ‘‘classical’’ or ‘‘resting’’ MO,
and express CCR2, CD64, CD62L. The best documented
function of ‘‘classical’’ MO is the removal and recycling of
apoptotic neutrophils at sites of inflammation [12]. It has recently
been reported that CD16+MO present different levels of CD14
expression [13] and correspond to two sub-groups of cells. The
CD14dimCD16+secrete Tumor Necrosis Factor-a (TNF-a) [14]
and correspond to ‘‘pro-inflammatory’’ MO, whereas the CD14hi
CD16+, sometimes called ‘‘intermediate’’ MO, exhibit intense
HLA-DR expression [15] and, as main producers of IL-10, might
represent an ‘‘anti-inflammatory’’ component of the MO subsets
induced in response to infectious pathogens. The two CD16+MO
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subsets greatly expand in various infectious and inflammatory
diseases and differ not only in phenotype but also in function. An
increase in the proportion of CD16+MO expressing higher CCR5
levels than CD14hiCD162MO has been reported in P. falciparum
infected pregnant women [16] and a potential role for CD16+MO
in the pathogenesis of maternal malaria has also been suspected
[16,17]. Nevertheless, the precise pathophysiological role of this
CD16+CCR5+MO subset remains unclear [18] and the
functional significance of changes in MO phenotypes in different
presentations of clinical malaria is unclear [19].
As in all infectious and inflammatory situations, the balance
between the pro- and anti-inflammatory MO subsets is strongly
regulated and this balance may influence the parasitological and
clinical outcomes of human malaria episodes, so that character-
izing changes occurring in the MO subsets and functional
phenotype during acute malaria infection would allow an
assessment of the contribution of diverse cell populations to
infection and the inflammatory response [20]. The Triggering
Receptor Expressed on Myeloid Cells–1 (TREM-1) is a marker of
activated MO. This transmembrane receptor was recently
implicated as having a critical role in regulating the function of
activated neutrophils and MO/ macrophages in both innate and
adaptive immunity [21]. TREM-1 is able to enhance the secretion
of pro-inflammatory cytokines during acute inflammation and/or
bacterial or fungal infection [22], but its involvement in human
malaria has not been determined.
Blood MO contribute to defense, at least in part by clearance of
iRBC [23,24], but they may contribute to pathology [25,26].
However the balance between the opposing effects is poorly
understood, as available information about changes in blood MO
phenotypes and functions during malaria attacks are still limited
and sometimes conflicting. If the failure to control infection at a
very early stage of infection is related to a lack in adequate innate
immune responses [27], a detailed knowledge of the parasite-host
factors involved in activating and regulating innate immune
responses may illuminate how the host innate immune system
responds to and/or is manipulated by Plasmodium infections
[28,29].
We hypothesized that discrete MO subpopulations were
induced during malaria infections and associated with anti-
parasitic activity. In the present study we carried out ex vivo
studies of blood MO phenotypes and of the in vitro functional
activities of the circulating myeloid cells found during acute
episodes of uncomplicated malaria attacks in patients living on the
Thai-Burmese border. We found that the balance between
different blood MO subsets varied dramatically among patients,
was associated with different functional anti-parasite activity by
ADCI and with levels of peripheral blood parasitemia.
Results
Inflammatory blood MO are increased during acute
uncomplicated malaria infections
The FSC/SSC gating parameters used to distinguish between
the proportions of the different leukocyte subsets and select the
MO area are shown in Figure 1A. Three different MO subsets
were identified in patients with acute uncomplicated malaria by
CD14 and CD16 expression levels (Figure 1B and 1C). Classical
MO display CD16 fluorescence intensity (FI) of less than 20
(Figure 1B and 1C). MO with a CD16 FI higher than 20 were
considered as ‘‘inflammatory’’ MO. The CD14 expression levels
defined two subsets of CD16+MO: ‘‘intermediate’’ MO (CD14hi
CD16+) displayed a CD14 FI greater than 100, whereas ‘‘pro-
inflammatory’’ MO (CD14dimCD16+) had a CD14 FI of less than
100 (Figure 1B and 1C).
In healthy, malaria-exposed individuals resident on the Thai-
Burmeseborder,themean
6,24561,191 ml21and that of MO was 3716133 MO ml21. Only
limited percentages and numbers of CD16+MO were detected and
mostcellsbelongedtotheclassicalMOsubsetwithameanCD14FI
of 126.1. Surprisingly, 98.4% of total blood MO of the healthy
malaria-exposed individuals were TREM-1 positive (Table 1),
indicating that MO from these individuals were activated.
In patients with acute uncomplicated malaria attacks, the mean
number of leukocytes was 8,24963,104 ml21and that of MO was
5916324 ml21. In contrast to the healthy malaria exposed
individuals, the circulating MO sub-populations of patients were
characterized by a 1.9 fold decrease in the percentage of classical
MO subset, a 8.7 fold increase in the intermediate MO subset and
a 7.6 fold increase in the pro-inflammatory MO subset (Table 1).
Thus the proportion and the absolute number of both interme-
diate and pro-inflammatory MO subsets increased during acute
malaria infection. Moreover, MO from patients showed a
significantly increased expression levels of TREM-1, a marker of
inflammatory MO [30], compared to the healthy malaria-exposed
controls (Table 1). Taken together, these results showed a clear
indication of an increase in inflammatory MO subsets during
acute uncomplicated malaria.
number ofleukocytes was
CD14hiand CCR2+CX3CR1+markers characterize two
groups of patients with acute uncomplicated malaria
The mean level of CCR2 and CX3CR1 expression on the total
blood MO was three times higher in patients with acute
uncomplicated malaria (18.561.5%) than in healthy malaria
exposed individuals (6.064.8%). Furthermore, it appeared that
the expression of CCR2 and CX3CR1 in the CD14hiMO could
discriminate two groups of patients. In healthy malaria exposed
individuals, the percentage of CD14hiCCR2+CX3CR1+MO was
low (mean value: 5.2364.49%, 95% CI: 1.84–8.62). Using the
upper 95%CI level of these healthy individuals, we could divide
the 76 malaria patients into two groups, illustrated by represen-
tative examples (Figure 1D and 1E).
In Group 1 patients (19/76, 25%), the mean percentage of
CD14hiCCR2+CX3CR1+MO was 19.7669.99% (Figure 1D),
i.e. almost 3.78 fold higher than in healthy individuals. Compared
to healthy malaria-exposed individuals, these patients displayed a
1.6 fold decrease in the mean percentage of classical MO, but a
8.1 fold increase in the mean percentage of intermediate MO and
Author Summary
Blood monocytes (MO) belong to the first line of defense
against infectious pathogens, but little is known of MO
phenotype and function during acute malaria infection. In
patients with acute uncomplicated malaria, we identified a
unique, and so far not described, minor population of MO.
The percentage and absolute number of MO with this
unusual phenotype was high in patients with low level of
blood parasitemia, suggesting that activation of this
particular subset of blood MO was potentially associated
with the control of parasite infection. Indeed, the MO from
these patients were the most efficient in the assay of
antibody- and cellular-dependent inhibition of parasite
multiplication (ADCI). These results support the hypothesis
that discrete MO subpopulations are induced during
malaria infection and are associated with anti-parasitic
activity.
Monocytes in Acute P. falciparum Malaria
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a 6 fold increase in the mean percentage of pro-inflammatory MO
(Table 1).
In Group 2 patients (57/76, 75%), the mean percentage of CD14hi
CCR2+CX3CR1+MO was 3.5162.42% (Figure 1E), i.e. similar to
that found in healthy controls. Compared to healthy malaria-exposed
individuals, patients in this group showed a 1.97 fold decrease in the
percentage of classical MO, an 9 fold increase in the percentage of
intermediate MO and an 8 fold increase in the percentages of pro-
inflammatory MO. Group 2 patients had 2.6 times more pro-
inflammatory MO than intermediate MO , versus 2.1 in group 1
(Table 1).The highest mean percentage and mean absolute number of
CCR2+CX3CR1+total blood MO were present in Group 1 patients
(Table 2); in addition, the mean percentage and absolute number of
CCR2+CX3CR1+MO were significantly greater in Group 1 patients
Figure 1. MO subsets identified in patients with acute uncomplicated malaria. (A) FSC/SSC parameters used to gate blood MO among
other leukocytes. (B and C): ‘‘Classical’’ MO (CD14hiCD162cells, blue dots), ‘‘intermediate’’ MO (CD14hiCD16+cells, green dots) and ‘‘pro-
inflammatory’’ MO (CD14dimCD16+cells, pink dots) staining found in the blood of Thai patients with acute uncomplicated clinical malaria are shown.
(B) In some patients, defined as Group 1, CD14hiCD16+intermediate MO dominated. (C) In other, clinically similar patients, and corresponding to
Group 2, CD14dimCD16+pro-inflammatory MO dominated, CD14 FI was weak and cells were scattered. (D and E) Respective percentages of CCR2
and CX3CR1 positive cells found in each of the three blood MO subsets.
doi:10.1371/journal.ppat.1000631.g001
Table 1. Percentages and absolute numbers of MO subsets found in patients during acute uncomplicated malaria attacks.
Donors Categories
Mean6 6SD monocyte subsets (%) and mean6 6SD MO
numbers per microliter TREM-1+ +
Classical IntermediatePro-inflammatory% cells FI
Malaria-exposed individuals Healthy (n=10)91.462.5 1.661.2 4.661.9 98.461.746.265.8
3396124765 17683646127
Acute uncomplicatedPatients (n=76)48.9619.5*** 1469.5***34.8618.1*** 94.569.2 73.8637.2***
287619583684***2056169*** 5596310*
Group 1 Patients (n=19)57.1621.3*** 12.969.5** 27.6619.8*** 92.3611.1* 58.9630.3
360624280681*** 1466124***5516290
Group 2 Patients (n=57)46.4618***14.469.5*** 37.1617.0***95.368.5* 78.6638.2**
260616984685 ***2276179***,1
5626318
Percentages and numbers of the different MO subsets and TREM-1 positive cells found in 10 healthy malaria-exposed individuals and in the two groups of patients with
clinically defined acute uncomplicated malaria attacks.
Values correspond to the mean percentages and/or numbers61SD and to the geometric mean of Fluorescence Intensity (FI). The differences between results were
tested by non-parametric 1 way median test between healthy malaria-exposed individuals (n=10) and Group 1 (n=19) or Group 2 patients (n=57). Significance levels
are indicated by star symbols as follows: * when p,0.05 and .0.01; ** when p,0.01 and .0.001, and *** when p,0.0001. Results of statistical tests between the two
groups of patients are indicated by circle symbol as follows:1when p,0.05.
doi:10.1371/journal.ppat.1000631.t001
Monocytes in Acute P. falciparum Malaria
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compared with Group 2 patients among the classical and intermediate
Mo but not in the pro-inflammatory subset (shown in Supporting
Information as SI Table 1), all these findings being consistent with the
definition of the two groups.
Finally, we noted that MO of Group 1 patients were
comparable to those of healthy individuals with regard to cell
size and granularity. In contrast, MO of Group 2 patients had a
greater size and a higher granularity than MO of Group 1 patients
while expressing lower levels of CD14 (Figure 1C).
Expression of membrane bound IFN-c and
transmembrane TNF-a
We examined the expression of CD56, membrane-bound IFN-c
and transmembrane TNF-a (mIFN-c and mTNF-a) in the MO
and their major subsets in the peripheral blood of patients with
malaria and healthy controls from malaria-endemic areas. The
proportions of CD56 positive and mIFN-c positive MO were low
in malaria patients compared to healthy malaria-exposed
individuals, while the proportion of mTNF-a MO were similar
(Table 2). Within the 3 main subsets of ‘intermediate’, ‘pro-
inflammatory’ or classical MO, there were major differences
between Group 1 and 2 patients concerning the markers
CCR2+CX3CR1+, as expected (Supporting Information: see
Table S1). In the classical MO, low percentages of CD56,
mIFN-c, and mTNF-a positive MO were observed in both groups
of malaria patients, particularly in Group 2 patients, compared
with the control group. In contrast, among the intermediate and
pro-inflammatory MO there was a very high percentage of CD56
and mIFN-c positive MO, and to a lesser extent, a high
percentage of mTNF-a positive MO particularly in Group 2
patients, compared with the control group. However, there were
no significant differences detectable between the two groups of
patients regarding the CD56, mIFN-c and mTNF-a labeling of
the three MO subsets, as summarized in Table S1.
Plasma cytokine levels are increased in the 2 groups of
patients
As no difference in the surface staining of MO was found
between the two groups of patients, we tested if they differed with
regard to circulating levels of cytokines or chemokines, but this was
not the case.
Indeed, cytokine and/or chemokine plasma levels in patients
differed from levels determined in healthy, malaria-naive individuals
(Table 3). For example, in Group 1 patients, significant increases in
IL-1b, IL-6, IL-10, TNF-a and MCP-1 mean concentrations were
found (Table 3). In Group 2 patients, this trend was even more
pronounced with mean increased levels of IL-1b, IL-6, IL-10, IL-
12p70, TNF-a and MCP-1 as compared to controls.
The concentration of IL-12p70 was marginally higher in Group
2 than in Group 1 patients but these differences fell just short of
statistical significance (p=0.0637).
Table 2. Phenotypic characterization of blood MO from healthy malaria-exposed individuals and patients with acute
uncomplicated malaria.
Surface markers Mean6 6SD total blood MO % and Mean6 6SD MO numbers per microliter
Healthy malaria-exposed donorsAcute malaria patients
Group 1 Group 2
CD56 60627.8 37.3634.444632.4
222614722162662646287
mIFN-c
54.4629.230.5631.531.1627.7
202614717362522046261
mTNF-a
13.4617.5 13.7611.716.9618.9
4664271658 1076157
CCR2+ CX3CR1+
6.064.830.8614.1***14.5610.4 ***,1
246171866130***85687**,1
The phenotypes of blood MO from healthy malaria-exposed individuals and from the 2 groups of patients with acute uncomplicated clinical malaria attacks were
determined by flow cytometry. Values correspond to the mean percentages 61SD and the differences between results were tested by non-parametric 1 way median
test between healthy malaria exposed individuals (n=10) and Group 1 (n=19) or Group 2 patients (n=57). Significance levels are indicated by star symbols as follows:
** when p,0.01 and .0.001, and *** when p,0.0001.
Results of statistical tests between the two groups of patients are indicated by1when p,=0.01
doi:10.1371/journal.ppat.1000631.t002
Table 3. Comparison of plasma cytokine or chemokine levels
found in the two groups of patients.
TypesGeometric means6 6SD of cytokines or chemokines (pg/ml)
Control individualsGroup 1 patients Group 2 patients
IL-1b
1.661.34.3663.23 * 3.6562.03 **
IL-6 2.863.023.3365.14 *30.4166.82 **
IL-8 3465.114.6962.0420.2363.81
IL-10 1.861.287.5065.26 ***93.7664.25 ***
IL-12p701.8761.14 1.9261.272.4161.38 ***
IFN-c
2.1961.181.9066.48 4.4163.18
TNF-a
1.6361.13 2.8362.43 **2.4761.59 ***
MCP-150.1261.69239.963.43 **426.6063.93 ***
The cytokine and chemokine concentrations in the serum of 13 Group 1 and 54
Group 2 patients were determined by flow cytometry (using CBA flex setH). All
the available plasma samples were tested at the same time and the differences
between concentrations were determined by non parametric 1 way median
Tests between Group 1 or Group 2 patients. 10 control individuals (healthy
malaria naı ¨ve individuals) were also tested and, as expected, cytokine or
chemokine concentrations differed from those found in patients, Significance
levels are indicated by star symbols as follows: * p,0.05, ** p,0.01 and
*** p,0.001.
doi:10.1371/journal.ppat.1000631.t003
Monocytes in Acute P. falciparum Malaria
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In the 76 patients, IL-1b and TNF-a levels were strongly
correlated (R2=0.957) and weaker but significant correlations
were observed between IL-6 and IL-8 and between IFN-c and IL-
8 (R2=0.494 and 0.375 respectively).
The two groups of patients defined by MO subsets differ
by parasite load and the stage of circulating parasites
We wondered if the two different distributions of MO
phenotypes in patients with malaria were related to different
densities of circulating parasites. We found that peripheral blood
parasitemia levels at admission were higher in Group 2 than in
Group 1 patients. The mean6SD parasitemia was 0.1460.34%
and 1.3063.34% in Group 1 and in Group 2 patients, respectively
(p=0.0053). However, the ranges of parasitemias were wide,
especially in Group 2 patients (Figure 2). So, at the individual level,
the MO phenotype was not predictive of parasite densities.
In addition, the relative level of maturation of circulating
parasites differed between patients. Blood parasites were exclu-
sively at the ring stage in 63.15% of the slides (12 out of the 19)
from Group 1 patients but in only 22.08% (13 out of 57 slides) of
thebloodsmears fromGroup
square=4.88, p=0.03). These observations led us to compare
the anti-parasite functional capacities of peripheral blood MO in
patients from Group 1 and 2.
2patients(Pearson Chi
Blood MO from Group 1 and Group 2 patients differed in
antibody-dependent parasite growth inhibition assays
MO from healthy malaria-exposed individuals and from
malaria patients were compared for their in vitro inhibitory effect
on the growth of falciparum parasites with and without IgG
(Figure 3). When MO of 12 healthy European malaria-naı ¨ve
individuals were used alone without IgG, they exerted no or only
very limited directgrowth
3.864.3%). In contrast, MO from 10 healthy malaria exposed
individuals inhibited parasite growth by 27.5611.0%, hence, they
appeared to be 7.2 fold more active than MO from healthy but
malaria-naı ¨ve individuals. It was notable that, the direct inhibitory
effect of MO from patients was lower than that of the healthy
malaria-exposed individuals, being 10.8611.7% and 17.4616.0%
for patients from Group 1 and Group 2, respectively. However, in
inhibitioneffects(mean6SD:
the presence of immune IgG (PIAG), to measure ADCI, the mean
parasite growth inhibition was 40.7764.22% (95%CI: 32.35–
49.19%) with MO from Group 1 patients and 22.3862.48% (95%
CI: 17.43–27.33%) with MO from Group 2 patients (p=0.0174).
The specific growth inhibitory index (SGI) was calculated for all
these ADCI assays. In healthy malaria-exposed individuals, the
mean SGI was 7.9967.93% [95% CI; 2.31–13.67%]. For Group
1 patients the mean SGI was 29.54630.74% [95% CI; 14.72–
44.35%] and it was significantly greater than the SGI from MO of
Group 2 patients (3.4165.78% [1.85–4.97%] (p,0.0001)). In
conclusion, an antibody and monocyte-dependent inhibition of
parasite multiplication (ADCI) was observed with the MO from
Group 1 patients only.
In order to limit a residual effect of parasite-specific and
membrane bound immunoglobulins, MO were thoroughly washed
before performing the inhibition experiments. Furthermore, when
anti-parasite antibodies titers were determined, no significant
differences were found between Group 1 and Group 2 patients as
defined by their MO subsets (see above). Anti-P. falciparum
Arbitrary Units AU for total IgGs were 1.7461.14 and
1.8161.04 (p=0.851), for IgG1 3.964.08 and 5.2863.52
(p=0.5551) and for IgG35.4265.76 and 4.92645.03 (p=0.552)
in Group 1 and Group 2 patients, respectively. Thus differences in
anti-malarial antibody titers were very unlikely to have been
responsible for the observed differences in parasite growth
inhibition.
In patients, ADCI activity was high when the percentage
of CD14hiCCR2+CX3CR1+MO was elevated
As mentioned above, an ADCI effect was observed with MO
from Group 1 patients only. More precisely, 10 out of 19 Group 1
patients had ADCI results above 20%, a situation associated with
significantly low parasitemias (Figure 2). Therefore, Group 1
patients from this malaria endemic area of Thailand, initially
delineated exclusively on the basis of a singular MO phenotype,
also had a distinct difference in functional ADCI anti-parasite
biological activity.
Figure 2. Distribution of peripheral parasitemia in patients
with acute uncomplicated malaria. Individual parasitemia levels
determined in 19 Group 1 and 57 Group 2 patients with clinically
defined acute uncomplicated malaria attacks are shown.
doi:10.1371/journal.ppat.1000631.g002
Figure 3. Growth inhibition of parasite cultures by MO from
patients with malaria. The percentage of P. falciparum growth
inhibition is shown firstly, with MO but without (w/o) purified immune
IgG and secondly, in the presence of MO plus purified immune IgG
(PIAG). Data represent the mean percentages of parasite growth
inhibition695% CI.
doi:10.1371/journal.ppat.1000631.g003
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To further characterize the phenotype of MO with ADCI
activity, MO from Group 1 patients were analyzed in greater
detail, by comparing the 10 individuals with MO active in ADCI
with the 9 individuals with no ADCI activity. As shown in Table 4,
MO activity evaluated by ADCI was simultaneously associated
with a high percentage of classical MO subset and with a low
percentage and a low absolute number of pro-inflammatory MO
subset. MO from patients with high levels of ADCI contained as
much as 72% of classical MO, and these MO with strong ADCI
activity showed significantly greater expression of CCR2,
CX3CR1, mTNF-a, CD56, and mIFN-c than MO with no
ADCI activity (Table 4). These results suggested that, in patients,
ADCI activity is associated with a particular MO subset,
expressing CCR2 and CX3CR1, mTNF-a, CD56 and mIFN-c.
Discussion
We have shown for the first time distinct differences in the MO
subsets in patients with acute malaria and healthy malaria-exposed
controls. Furthermore, we have shown that patients with high
numbers of CD14hiCCR2+CX3CR1+MO had lower parasit-
emias thanpatientswith
CCR2+CX3CR1+MO. Our results suggest this is a causal
association as circulating MO expressing CCR2, CX3CR1,
CD56, mTNF-a and mIFN-c are not only associated with lower
parasitemias but also are associated with strong ADCI activity.
Since the historical observations of Talliaferro, MO and
macrophages have been largely looked upon as phagocytic cells
in malaria infections, clearing parasites with or without opsonizing
antibodies. After a long era which concentrated almost solely on
the role of lymphocytes in host immune responses, conceding an
additional role to MO as antigen-presenting cells, this myeloid
lineage are now perceived as comprising a very wide number of
distinct cell subsets, with distinct phenotypes and numerous
low numbersof CD14hi
important functions. Nevertheless, the precise functional correlates
of MO subsets defined by surface phenotype are far less defined
than the functions of lymphocyte subsets.
Given the outstandingly high foreign parasite mass circulating
in the blood during acute falciparum malaria and the strong
induction of IFN-c by both pre-erythrocytic stage and by blood-
stage parasites, potentially leading to a very strong pro-
inflammatory stimulus, there are ample reasons to analyze changes
in MO numbers, phenotypes and function during malaria. We
have shown substantial changes in MO phenotypes in non-
infected populations living in endemic areas and also changes in
MO phenotypes in acute uncomplicated malaria cases in adults.
Our results reveal several biologically significant modifications in
phenotype, cytokine-chemokine expression and activity of patients’
MO. In particular, we have shown that infection in patients with a
similar clinical presentation can result in the induction of two
distinct MO phenotypes that can be distinguished by a single set of
markers, but show quite different, possibly opposing, biological
anti-parasite activity. Blood MO of malaria-exposed but non-
infected individuals were significantly more mature and more
activated than those from Europeans controls. In our study MO
from malaria-exposed individuals showed markedly increased
expression of CD56, mIFN-c and mTNF-a, TREM-1 and HLA-
DR, in the classical MO subset. The CD56 and CD33 positive
MO have been associated with higher HLA-DR expression [31].
Others have described an increase in the CCR5 expression of
circulating MO in Italian expatriates living in malaria endemic
areas [32]. These studies do not determine the origin of these
changes in MO sub-populations. It may be that these changes
reflect the long term consequences of previous malaria episodes, or
are, as proposed by others, due to so-called ‘‘environmental
factors’’, such as exposure to mosquito bites and saliva [32] or
even induced by increased IFN-c stimulated by chronic viral
infections prevalent in malaria-endemic areas [33]. Whatever the
Table 4. Phenotypic characterization of blood MO from group 1 patients with or without ADCI activity.
CategoriesSurface markers% 10 patients with ADCI activity9 patients with no ADCIp values
* SGI%51.6627.1 5.164.2p=0.0001
Parasitemia%0.01860.029 0.2864.47p=0.0008
Classical MOCD14hiCD162
72.1614.9%38.3613.3%p=0.0035
4846255 /ml2236137 /mlp=0.0427
CD5622.7625.5% 0.560.9%p=0.0427
1316217 /ml468 /mlp=0.0427
mIFN-c
21.6627.8%0.260.4%p=0.0220
1216223 /ml264 /mlp=0.0220
mTNF-a
2.162.8%0p=0.0001
15622 /ml0p=0.0016
CCR2+CX3CR1+
16.966.8%5.463.1%p=0.0427
102659 /ml 29624 mlp=0.0085
Intermediate MOCD14hiCD16+
11.869.5%14.0610.0%p=0.509
74672 /ml87694 /mlp=0.814
Pro-inflammatory MO CD14dimCD16+
13.567.9 (%) 43.961 7.1 (%)p=0.0008
75645 (/ml)2166131 (/ml)p=0.0095
*SGI%=The parasite specific growth inhibition (i.e. the ADCI effect) was calculated as indicated in the Material and Methods section.
The 19 patients from Group 1 were tested with regard to ADCI activity.
Ten patients had a positive ADCI activity (with SGI.20%), and 9 patients had a negative ADCI activity. MO phenotypes were tested and compared for various surface
marker expressions. Differences in staining were found in the classical and the pro-inflammatory MO subsets as indicated. The statistical analyses were performed by
non-parametric 1 way median tests.
doi:10.1371/journal.ppat.1000631.t004
Monocytes in Acute P. falciparum Malaria
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reason for the induction of these cells, the distinctive MO
phenotype associated with infection led us to analyze the
functional associations of MO subsets during falciparum malaria.
As expected blood MO from acute malaria patients had several
characteristics of inflammatory MO, with an overall increase in
the percentage of CD16+MO, and in secreted inflammatory
cytokines, with a substantial and significant decrease in the
percentage of classical MO and a corresponding increase in both
intermediate and pro-inflammatory MO. Patients’ MO had
significantly lower percentages of CD56 and mIFN-c and higher
percentages of CCR2+CX3CR1+than malaria-exposed individu-
als, and high expression of the inflammatory marker TREM-1.
Given the large range of markers we used to define MO subsets,
results are difficult to relate to other studies. However, our data are
consistent with more limited previous studies. In Malawi,
increased CD16+MO populations were described during malaria
infection [34]. In our study, among 76 patients with acute
uncomplicated malaria studied the major finding was the
characterization of two groups of patients with different MO
phenotypes. Group 1 patients, characterized by an elevated
percentage of CD14hiCCR2+CX3CR1+MO, had a low mean
parasitemia. Group 2 patients, characterized by a percentage of
CD14hiCCR2+CX3CR1+MO similar to that of healthy malaria
exposed individuals, had a pro-inflammatory phenotype, a trend
for higher levels of plasma cytokines, and a 10 fold higher mean
peripheral parasitemia. Finally, Group 1 and 2 MO differed in
their parasite inhibition activity in cooperation with effective
parasite-specific antibodies.
These observations raise two questions. First, is there a causal
relationship between those parameters and, second, are these
characteristics genetically determined, or do they reflect different
states in the course of a falciparum clinical attack? It is indeed
tempting to speculate that patients developing the predominantly
anti-inflammatory MO phenotype have lower parasitemia because
their MO are highly effective at achieving parasite inhibition in
cooperation with antibodies as in the ADCI mechanism, while
patients with the pro-inflammatory phenotype have higher mean
parasite densities as their MO are completely ineffective at
inhibiting parasite growth. The lack of a complete correspondence
between ADCI activity and parasitemia loads could be due, at
least in part, to the well-known poor association between
peripheral blood parasitemia and total parasite burden [35]. But
it may also be relevant that the stage of circulating parasite differed
between the two groups of patients. The presence of mature
parasites in the blood (which was more frequent in Group 2
patients) was consistent with similar indications independently
obtained recently in the same malaria endemic area [36].
There may be genetic factors that determine the degree and
direction of MO development during acute infection. Genetic
control of several innate and adaptive immune responses is
documented and individuals differ markedly in their susceptibility
to systemic infection, inflammatory states and in their ability to
mount a rapid pro-inflammatory cytokine response to malaria
infection [37]. However, it is also possible that the two groups may
not reflect genetic differences but temporal differences in the
innate response to falciparum parasites.
The initial rise in parasitemia can be expected to induce a very
strong pro-inflammatory response that may control parasite
growth. Indeed, activated macrophages are essential for host
survival in animal models of malaria [38]. However inflammatory
cytokines and free NO and O2 radicals triggered by parasite
material could also contribute to much of the pathology seen in
malaria [39], so that it is vital that anti-inflammatory responses are
induced to avoid excessive tissue damage [40]. Therefore, it is
possible that the initial pro-inflammatory response may be
represented in Group 2 patients and the subsequent anti-
inflammatory regulatory response represented by Group 1
patients. Whether the intriguing observation of lower parasitemia
seen in Group 1 is the result of a previous pro-inflammatory state
or more directly of functionally more effective ADCI activity in
MO, cannot be determined. Additional studies particularly with
follow-up of patients in different clinical presentations and
epidemiological situations are now obviously required.
Results from falciparum growth inhibition studies are interesting
and pose many questions. Antibodies effective in the MO-mediated
antibody-dependent ADCI mechanism have been extensively
studied [41–43] but these studies have always used MO from
healthy European blood donors. Whether MO isolated from
patients during a malaria attack also retain ADCI activity had not
beenaddressed. Here, we have shown that somebutnotallpatients’
MO can exert strong ADCI activity. The low or absent ADCI
activity of pro-inflammatory MO from Group 2 patients is
consistent with our previous observations that activated MO from
donors suffering from a viral infection or activated macrophages
derived from normal blood MO by adherence in vitro over 48–
72 hours, had low activity in ADCI assays [44]. Conversely, MO
which are activated by classical pro-inflammatory stimuli may exert
a direct, antibody-independent, anti-parasite effect seen in MO
from exposed endemic area donors and here to a lesser extent in
MO from Group 2 patients, in contrast to the low direct, antibody-
independent anti-parasite effect of MO from healthy European
donors. Though non-opsonic clearance of iRBCs do occur [45,46],
the very low MO/RBC ratio in ADCI assays suggests that
mediators released by activated MO, including chemokines,
cytokines and free radicals, must play a more prominent role.
Above all, the characterization of patients MO with distinct
differentiation and activation states led us to identify far more
precisely the features of the blood MO subset most effective at
mediating ADCI. Our observation of the MO subset with
increased CCR2+CX3CR1+, mTNF-a and CD56 expression as
having critical ADCI activity, complements our in vitro studies
showing that the co-activation of both CD32 and CD16 was
required for ADCI [47]. No similar increase in double positive
MO has been reported in other infectious diseases.
In conclusion, MO and macrophages have multiple functions
during patent falciparum parasitemia. In response to parasite-driven
signals, they adapt to directly reduce parasite loads in an antibody-
independent manner, to initiate and later to regulate adaptive
immune responses, to remove infected RBC by antibody-
dependent opsonization and by the ADCI mechanism. The
present study provides several new valuable insights into both the
initial and last steps of this series of actions. In patients with acute
malaria, we have shown two distinct MO phenotypes with
correspondingly different ADCI phenotypes. This work comple-
ments decades of studies concentrating on T-cells and antibodies,
and paves the way for further characterization of dynamic studies
of MO subsets and functions during malaria infection.
Materials and Methods
Study site and individuals tested
We studied indigenous malaria patients living in Thai-Burmese
border. Seventy six patients (27.7610.1 years old) with uncompli-
cated falciparum malaria, i.e. with fever .37.5uC but without
features of severe or complicated disease and with a mean
parasitemia of 1.0162.93% and 10 healthy malaria-exposed
individuals (26.266.9 years old) with negative blood smears were
enrolled in this study during the 2007 transmission season. These
Monocytes in Acute P. falciparum Malaria
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Page 8

patients had not been treated before admission, had no other cause
of disease than malaria identified at enrollment and they recovered
afteranti-malariatreatment. Five to10 mlofbloodweretaken from
patients or healthy individuals. Written informed consent was
obtained from all participants after detailed explanations of the
studies in the local language. This protocol was approved by the
Research Ethics Committee, Faculty of Medicine Siriraj Hospital,
Mahidol University, Thailand. Blood samples from 12 malaria
naı ¨ve individuals (29.4265.14 years old) living in France were
obtained from the blood bank in Paris, with the consent of the
Pasteur Institute Ethical Committee, Paris, France.
Parasite cultures
The P. falciparum laboratory strain TM267 [48] was obtained
from Dr. Kesinee Chotivanich (Mahidol University, Thailand) and
previously used for other studies. TM267 is a knobless parasite
strain which is unable to bind endothelia and specific host ligands.
Parasite cultures were regularly checked by PCR to exclude
mycoplasma contamination and maintained in Group O+human
RBC at 37uC with 5% CO2suspended in RPMI medium 1640
(Sigma, Germany) containing either 10% heat-inactivated AB+
human serum (for routine cultures) or 10% Albumax (GIBCO,
USA) (before ADCI experiments).
Monocyte surface staining
The phenotype of cells were determined by direct immunoflu-
orescence with monoclonal antibodies (mAbs) to CD14, CD16,
CD33, HLA-DR, CD56, CD16, IFN-c-, and TNF-a conjugated
with fluorescein isothyocyanate (FITC), phycoerythrin (PE), and
peridinin chlorophyll protein (PerCP) (BD Bioscience, Oxford,
UK) and mAbs to CCR2, TREM-1 (Serotec, Oxford, UK), and
CX3CR1 (MBL, Nagoya, Japan) conjugated with APC, PE, and
FITC, respectively, following the manufacturer’s protocols.
Isotype matched controls were used in all experiments.
Two hundred microliters of well-mixed whole blood from each
patient sample wasused for eachanalysis.Of note, the totality of the
200 ml of blood were systematically passed through the instrument,
hence, between 30,000 and 60,000 blood MO of each blood sample
were counted. Three color analysis was performed with CD14,
CD16, and CD33 or HLA-DR or IFN-c, or TNF-a or TREM-1 or
CD56. In the latter case, only MO with low FI of CD56 were
acquired. Four colors analysis was used to determine CD14, CD16,
CCR2 and CX3CR1 expression. Using a FACSCalibur (Becton
Dickinson, NJ, USA), MO were first identified and gated by side
and forward scattering. Final gates to exclude NK cells but
including CD14, CD33 and TREM-1 positive cells were then
defined [21] and used throughout the study.
Determination of parasite-specific IgG by ELISA
Total IgG and subclasses were determined by ELISA in 96 well
MaxisorbH plates (Nunc, Paris, France) [49] with anti-IgG1 (clone
NL16) and anti-IgG3 (clone ZG4) mAbs (Skybio, Cambridge, UK).
Lysates of Plasmagel enriched mature malaria infected RBCs were
used as antigen [50]. A pool of immune sera from Africa and a pool
of malaria-naı ¨ve Europeans’ sera were used as controls. The specific
reactivity of each serum sample was expressed as a ratio (thus
Arbitrary Units) obtained by dividing the OD obtained from each
test serum by the mean OD obtained from 6 negative control sera.
Antibody and monocyte-dependent inhibition of
parasite multiplication (ADCI)
The ability of each patient’s MO to inhibit the in vitro growth of
parasites was evaluated either with no IgG, with IgGs purified from
a pool of sera obtained from healthy donors never exposed to
malaria(NIgG),or with immune IgG purified (PIAG)from a pool of
333 adults from Ivory Coast. The ADCI assays followed the
protocol previously described [6], with minor modifications, as
indicated below. For MO preparation, cell suspensions obtained
after Histopaque were adjusted to 46106MO ml21in RPMI 1640
without serum. Then 100 ml of cell suspension with 10% Albumax
were distributed into wells of a sterile 96-well flat bottom plate
(Nunc,France)andincubatedfor309at37uCand in5%CO2.Non-
adherentcellswereremovedbygentlywashingeach wellthricewith
200 ml ofRPMI1640andtheplateswereturnedupsidedownatthe
end of each washing so that only cells adhering to the bottom of the
wells remained whereas most contaminant cells were eliminated.
Both CD14+CD162and CD14+CD16+MO remained attached
and satisfactorily reflected the initial proportion of the different
blood MO identified and present in each patient’s blood (as
illustrated in Supporting Information Figures S1 and S2). Each
ADCI test used 50 ml of either asynchronized 0.5% parasite culture
(in the test wells) or uninfected red blood cells (uRBC) (in the control
wells) diluted at a final 2.5%hematocrit.Ten ml of eitherimmune or
normal, purified IgG or RPMI were added into the test or control
wells respectively. RPMI 1640 with 10% Albumax was added to
final volume of 200 ml. The parasite cultures were maintained at
37uC for 72 hours in 5% CO2. All tests and controls were
performed in duplicate and parasitemia was assessed by flow
cytometry as described [42].
Cytokine detection
Cytometric bead arrays (CBA) (BD Biosciences, Oxford, UK)
were used to measure MCP-1, IL-1b, IL-6, IL-8, IL-10, IL-12b,
IFN-c and TNF-a following the manufacturer’s instructions.
Plasma samples were separated from whole blood by centrifuga-
tion, kept at 220uC and tested at the same time. Standard curves
for each cytokine were generated by using the reference cytokine
concentrations supplied with the kits. Raw data were analyzed
with the CBA Software to obtain concentration values as described
by Jimenez et al [51].
Statistical analysis
Univariate and multivariate analyses were carried out using
Statview5H, SPSS16H or JMPH softwares. Non-parametric (one
way median test) or parametric tests (t test) were used to compare
the different Groups where appropriate and a p,0.05 was
considered as significant.
Supporting Information
Figure S1
shows CD14 positive cells and Figure 1B is an overlay of light
transmission microscopy and fluorescent cells (objective 606). The
white arrow shows a CD14hiMO and the black arrow shows a
CD14dimMO.
Found at: doi:10.1371/journal.ppat.1000631.s001 (2.34 MB PDF)
Adherence of CD14+(CD14hiand CD14dim) CD16+
MO. Figure 2A is a light transmission field. In Figure 2B, bright
cells were CD14+cells and in Figure 2C, bright cells correspond to
CD16+cells. Figure 2D is an overlay of CD14+and CD16+cells
(objective 406). By this technique we could identify CD14hiand
CD14dimMO and intermediate as well as pro-inflammatory MO
(data not shown).
Found at: doi:10.1371/journal.ppat.1000631.s002 (3.12 MB PDF)
Adherence of CD14hiand CD14dimMO. Figure 1A
Figure S2
Table S1
and double positive CCR2 and CX3CR1 expressed in each subset
Percentages and numbers of CD56, mIFN-c, mTNF-a
Monocytes in Acute P. falciparum Malaria
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Page 9

of blood MO. The percentages of blood MO positive for different
markers were determined in each MO subset. The mean
percentages 61SD of positive blood MO were obtained after
three color analysis (using anti-CD14, anti-CD16, and either anti-
CD56, or anti-mIFN-c anti-mIFN-c or anti-mTNF-a) or after
four color analysis (using simultaneously anti-CD14, anti-CD16,
anti-CCR2 and anti-CX3CR1 monoclonal antibodies). The
differences between results were tested by non-parametric 1 way
median test between healthy malaria exposed individuals (n=10)
and Group 1 (n=19) or Group 2 patients (n=57). Significance
levels are indicated by star symbols as follows: * when p,0.05
** when p,0.01 and *** when p,0.001. Results of statistical tests
between the two groups of patients are indicated by symbols as
follows: 1 when p,0.05; 11 when p,0.001 and 111 when
p,0.0001.
Found at: doi:10.1371/journal.ppat.1000631.s003 (0.04 MB PDF)
Acknowledgments
We would like to thank Dr. Genevieve Milon for most useful discussions,
Pierre Buffet, Marie-Noelle Ungeheuer and Kesinee Chotivanich for their
fructuous collaboration and for providing patients’ blood samples and the
technical support of the team of Prof. Pattanapanyasat, Center of
Excellence for Flow Cytometry, Siriraj Hospital.
Author Contributions
Conceived and designed the experiments: PC CR KP. Performed the
experiments: PC PS. Analyzed the data: PC CR PS JLP. Contributed
reagents/materials/analysis tools: KP. Wrote the paper: PC CR JLP DJR
PD. Responsible for statistics analyses: CR. Provided patient blood
samples: RR KP.
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PLoS Pathogens | www.plospathogens.org 10October 2009 | Volume 5 | Issue 10 | e1000631