Molecular Immunology 48 (2011) 1224–1235
Contents lists available at ScienceDirect
Molecular Immunology
journal homepage: www.elsevier.com/locate/molimm
Distribution and expression analysis of transcription factors in tissues and
progenitor cell populations of the goldfish (Carassius auratus L.)
in response to growth factors and pathogens
Barbara A. Katzenback a , Matthew Karpman a , Miodrag Belosevic a,b,∗
a
b
Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
School of Public Health, University of Alberta, Edmonton, Alberta, Canada
a r t i c l e
i n f o
Article history:
Received 28 January 2011
Received in revised form 1 March 2011
Accepted 8 March 2011
Available online 6 April 2011
Keywords:
Fish
Progenitor cells
Transcription factors
Gene expression
Kit ligand A
CSF-1
a b s t r a c t
We report on the mRNA levels of a panel of transcription factors in the kidney and spleen tissues, and
in the cell populations from the blood, the spleen, and in the sorted kidney progenitor cells. The mRNA
levels of cebp˛, cjun, cmyb, egr1, gata1, gata2, gata3, lmo2, mafb, pax5, pu.1 and runx1 were assessed in
healthy goldfish as well as in fish challenged with two different pathogens, Aeromonas salmonicida A449
or Trypanosoma carassii. Spleen tissue from healthy goldfish showed higher expression of myeloid (cjun),
erythroid (gata1) and lymphoid (gata3, pax5) transcription factors, and lower expression of the myeloid
transcription factor cebp˛ when compared to that of kidney. Splenocytes and PBLs had significantly higher
mRNA levels of the transcription factors involved in myeloid (pu.1, mafb, cjun, egr1, cebpa), erythroid
(gata1, lmo2), and lymphoid pathways (gata3 and pax5) compared to sorted kidney R1 progenitor cells,
while R1 progenitor cells had higher mRNA levels of early progenitor transcription factors (runx1 and
cmyb). Furthermore, the R1 progenitor cells had higher mRNA levels of the transcription factors involved
in early progenitor cells (egr1, gata2) and the lymphoid lineage progenitors (gata3, pax5) compared to
those in kidney. The mRNA levels of the transcription factors (gata2, mafb, cjun, gata1, lmo2, gata3, and
pax5) in R1 progenitor cells changed during cultivation; they were elevated in day 2 R1 cells and downregulated by day 6 of cultivation, when compared to those of day 0 R1 cells. Treatment of day 2 R1
progenitor cells with rgCSF-1 resulted in an up-regulation of transcription factors important for myeloid
cell development (cjun and egr1). Similarly, rgkitla up-regulated the expressions of myeloid (mafb, egr1
and cebpa) transcription factors. Changes in the expression of transcription factors in the R1 progenitor
cells were related to the observed developmental processes of myeloid progenitor cells during cultivation
or treatment with recombinant growth factors in vitro. We also observed differential expressions of
the transcription factors in R1 progenitor cells following exposure of the goldfish to either prokaryotic
(heat-killed A. salmonicida A449) or eukaryotic (T. carassii) pathogens.
© 2011 Elsevier Ltd. All rights reserved.
1. Introduction
The commitment and differentiation of a hematopoietic stem
cell (HSC) or progenitor cell (HPC) into a functional mature cell is a
tightly regulated process directed by the modulation of transcription factors which then act to regulate gene expression (Cantor
and Orkin, 2002; Friedman, 2002; Ye and Graf, 2007; Zhu and
Emerson, 2002). Cytokines present in the cell niche influence this
process of HSCs/HPCs differentiation (Metcalf, 1998, 2008; Rieger
∗ Corresponding author at: CW-405 Biological Sciences Building, Department of
Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada.
Tel.: +1 780 492 1266; fax: +1 780 492/9234.
E-mail address: [email protected] (M. Belosevic).
0161-5890/$ – see front matter © 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.molimm.2011.03.007
et al., 2009). Cytokines important for the expansion, maturation
and development of precursors and mature cells include kit ligand, also known as stem cell factor, which is important for HSC
self renewal (reviewed in Kent et al., 2008), mast cell development,
and synergizes with other growth factors for the development of a
variety of cell types (reviewed in Ashman, 1999). Other cytokines
such as IL-3 and GM-CSF are important for the maintenance and
development of myeloid precursors, and the cytokines CSF-1 and
GCSF are required for the differentiation of precursors into monocytes/macrophages and granulocytes, respectively (Barreda et al.,
2004a).
The process of hematopoiesis responds to meet homeostatic
cell turn-over demands, or to “emergency” situations instigated
by an injury or infection to produce increased cell numbers of
a particular lineage to meet the demands of the insult (Fliedner
B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
and Graessle, 2008; Panopoulos and Watowich, 2008; Zhan et al.,
1998). Often the production of one cell lineage is at the expense
of another lineage; CSF-1 promotes monopoiesis at the expense
of granulopoiesis, while GCSF creates the reverse situation (Rieger
et al., 2009; Rieger and Schroeder, 2009). Ultimately, the action
of myelopoietic growth factors is mediated through the expression of transcription factors. One example is CSF-1, which has been
shown to induce Egr1 in mouse bone marrow derived progenitors,
an important transcriptional regulator in the development and differentiation of monocytes/macrophages (Carter and Tourtellotte,
2007; Krishnaraju et al., 2001). However, the expression of Egr1
antagonizes the transcription factor Gfi-1, which is important for
neutrophil differentiation (Laslo et al., 2006; Zarebski et al., 2008).
Many complex transcriptional networks involved in hematopoiesis
have been elucidated and can be used to identify the particular
stage of a cell within a lineage; one example is B-cell development
(Nutt et al., 1999).
In comparison, relatively little is known about teleost
hematopoiesis. In part, progress is hampered by the lack of
available reagents such as recombinant cytokines and antibodies. Alternatively, we can use transcription factors, which appear
to be conserved between higher and lower vertebrates to study
developmental pathways and this approach has been useful in
studying hematopoiesis in the zebrafish model system (Ellett and
Lieschke, 2010; Hsia and Zon, 2005; Paik and Zon, 2010; Zwollo
et al., 2010).
In this study, we cloned and sequenced a number of goldfish
transcription factors based on their involvement in the maintenance of HSCs/HPCs and in the differentiation of a HPC along
a myeloid, erythroid, or lymphoid pathway. The transcription
factors Runx1, cMyb, and GATA2 are involved in the activation
of myeloid genes and in the proliferation and maintenance of
multipotent progenitor cells (Hosoya et al., 2010; Loose et al.,
2007). The antagonism between PU.1 and GATA 1 regulates the
myeloid/erythroid pathway and they were chosen as key transcription factors involved in this lineage fate decision (Burda et al.,
2010). Egr1, cJun, and MafB were selected based on their involvement in monocyte/macrophage differentiation (Aziz et al., 2009;
Cai et al., 2008; Krishnaraju et al., 2001; Sarrazin et al., 2009), while
CEBP␣ was chosen for its essential role in granulocyte development (Zhang et al., 1997). GATA1 and Lmo2 were chosen for their
ability to direct erythroid fate decisions and positively regulate
erythroid differentiation (Brandt and Koury, 2009; Burda et al.,
2010), and lastly, Pax5 and GATA3 are involved in B-cell (Fuxa
and Busslinger, 2007) and T-cell (Hosoya et al., 2010) development,
respectively.
Our laboratory has previously developed a unique in vitro
primary kidney macrophage (PKM) culture system as a model
system for monopoiesis that possesses all three populations of
macrophage development: progenitor cells (R1s), monocytes (R3s),
and macrophages (R2s) (Neumann et al., 1998, 2000). The progenitor cells isolated from the kidney, the major hematopoietic
organ in teleosts, and are responsible for the generation of monocytes and macrophages. These cells are capable of proliferation and
differentiation due to the production of endogenous growth factors that regulate these processes (reviewed in Hanington et al.,
2009b). Of particular interest to our laboratory is the composition of the progenitor cell population, how these cells commit
to a monocyte/macrophage lineage in the presence of a complex
mixture of endogenous growth factors or defined cytokines, and
lastly, how this progenitor cell population changes in response to
pathogens in vivo. Therefore, the focus of this study was to examine these questions in relation to the goldfish kidney progenitor
cell population using the panel of transcription factors we identified as a means of understanding teleost myeloid progenitor cell
development.
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2. Materials and methods
2.1. Fish
Goldfish (Carassius auratus L.) approximately 3–4 in. in size were
obtained from Aquatic Imports (Calgary, AB) and maintained in
tanks with a continuous flow water system at 17 ◦ C and with a
14 h light/10 h dark period in the aquatic facilities of Biological Sciences building at the University of Alberta as previously described
(Katzenback et al., 2008). Fish were fed until satiated daily and were
acclimated for at least 3 weeks prior to use in the experiments. During this time period, fish were monitored for any signs of disease
to ensure fish were healthy. Only fish devoid of any signs of disease
for over 3 weeks were used in experiments. Prior to handling, fish
were sedated using a TMS (tricaine methane sulfonate) solution
of 40–50 mg/L in water. The animals in the Aquatic Facility were
maintained according to the guidelines of the Canadian Council of
Animal Care (CCAC-Canada).
2.2. Bacteria
Aeromonas salmonicida A449 was a kind gift from Dr. Jessica
Boyd (NRC Institute, Halifax, Canada) and is a virulent strain of
Aeromonas that possesses and an A layer and is autoaggregating as
previously described (Katzenback and Belosevic, 2009a). Glycerol
stocks of A. salmonicida A449 stored at −80 ◦ C were used to streak
Tryptic Soy Agar (TSA) + 20 ␮g/mL chloramphenicol (Sigma) plates
and incubated at 18 ◦ C for 72 h. A single colony was used to inoculate 5 mL of tryptic soy broth (TSB) + 20 ␮g/mL chloramphenicol
that was grown for 24 h at 18 ◦ C with shaking to stationary phase.
A 1:100 dilution of this culture was used to inoculate 100 mLs of
TSB + chloramphenicol and cultured at 18 ◦ C until mid-log phase.
Bacteria were harvested and washed twice in sterile 1x PBS. Due
to the autoaggregating nature of the bacteria, a sample of bacteria was serially diluted in TSB containing 1% SDS prior to plating
on TSA + chloramphenicol plates which mitigated clumping and
allowed for the enumeration of individual colony forming units
(CFUs). Plates were incubated for 48 h at 18 ◦ C and colonies counted.
A. salmonicida A449 was heat killed by incubating at 60 ◦ C for 45 min
in a water bath. Following heat killing, a sample of the bacteria
was plated on TSB + chloramphenicol plates to ensure bacteria were
non-viable. Heat killed A. salmonicida A449 was stored at −20 ◦ C
until used. The injection of fish with 1 × 109 heat-killed A. salmonicida was based on numbers used in previous literature in which
authors injected with 1 × 108 live Aeromonas (Zhang et al., 2011).
However, since we were dealing with heat-killed bacteria that
do not cause the same pathology as a live infection, we chose to
increase our dose to 1 × 109 bacteria/fish.
2.3. Trypanosomes
Trypanosoma carassii (strain TrCa) (syn. with T. danilewskyi) was
isolated from a crucian carp (C. carassius) by Dr. J. Lom in 1977. The
parasites were obtained from Dr. P.T.K. Woo, University of Guelph,
Ontario, Canada. Trypanosomes were maintained in vitro by our
laboratory as glycerol stocks at −80 ◦ C as well as serial passage
from a 6–7-day-old stock culture in TDL-15 medium containing 10%
heat-inactivated goldfish serum. Trypanosomes used for all assays
were cultured in vitro and used from 6 to 7-day-old stock cultures as
previously described (Bienek and Belosevic, 1997). Trypanosomes
were washed twice in serum-free TDL-15 medium, enumerated
using a hemacytometer to and re-suspended to 1 × 109 trypansomes/mL immediately prior to use in 3 days post infection (dpi)
experiments or 6.25 × 107 trypanosomes/mL for use in 7 dpi experiments. The infection dose of 100 ␮L of 6.25 × 107 trypanosomes/mL
(6.25 × 106 trypanosomes per fish) was selected based on our
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B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
Table 1
Primer sequences.
Sequence 5 –3
Q-PCR primers
CEBP␣ S
CEBP␣ AS
cJun S
cJun AS
cMyb S
cMyb AS
EF1␣ S
EF1␣ AS
Egr1 S
Egr1 AS
GATA1 S
GATA1 AS
GATA2 S
GATA2 AS
GATA3 S
GATA3 AS
Lmo2 S
Lmo2 AS
MafB S
MafB AS
Pax5 S
Pax5 AS
PU.1 S
PU.1 AS
Runx1 S
Runx1 AS
atcaaacaagagcctcgggaggaa
tggatttccctcgatcgccaatct
cggcgatccggttcct
cctctctcccccatcgacat
gggcttacggatgcattaaaga
gagcagggatgccttcca
ccgttgagatgcaccatgagt
ttgacagacacgttcttcacgtt
tatcctaaccggccaagcaagaca
tctgccgcatgtggatcttagtgt
gtctgttctggccgttcatttt
accagaggcacgtgaatgc
caccatcccatcccaaccta
gcttttgcatttgggtgtga
gtgtcccctgacccctcaat
cgactatgagcagaatccagctt
tgcgtgtccgtgacaaagtc
aaaaatgtcctgctcacacacaa
ccaacatcaacaccaacaatacg
gacccgggcgagatagga
atgagacgggcagcatcag
gatctcccaggcaaacatggt
tcgcctcctgttgttgatgtaa
cagtcgcagtcctccgttaga
tcaaggtagttgcccttggtgata
ttgaggagggtttgtgaagacggt
Vector specific primers
M13 forward
M13 reverse
T7 forward
BGH reverse
gtaaaacgacggccag
caggaaacagctatgac
taatacgactcactataggg
tagaaggcacagtcgagg
CSF-1 expression primers
CSF-1 sense
CSF-1 antisense
acacacacataacagcccacaaagcc
ggttcagtggtggattctgggta
blood leukocytes, four individual goldfish were bled from the caudal vein using a 25G needle and heparinized syringe to prevent
clotting. The blood was diluted 1:4 with MGFL-15 medium containing heparin, layered onto 51% percoll and centrifuged at 430 × g
for 25 min. Cells at the interface were washed 2 times with MGFL15 medium. RNA isolation from splenocytes and peripheral blood
leukocytes was performed using Trizol (Invitrogen) and cDNA synthesis performed using Superscript II (Invitrogen) according to the
manufacturers protocol. Quantitative PCR was performed using an
Applied Biosystems 7500 Fast Real-Time PCR machine and analyzed
using the delta delta Ct method. Elongation factor 1 alpha (EF1␣)
was used as the endogenous control.
2.6. Isolation and cultivation of goldfish primary kidney
macrophage (PKM) cultures
Goldfish (10–15 cm) were anesthetized with TMS, and sacrificed. The isolation and cultivation of goldfish kidney leukocytes
in complete NMGFL-15 medium supplemented with 5% carp
serum and 10% newborn calf serum was performed as previously
described (Neumann et al., 1998, 2000). Cells were cultured at 20 ◦ C
in the absence of CO2 . Primary kidney macrophage (PKM) cultures
are composed of three distinct cell populations consisting of early
progenitors (R1s), monocytes (R3s), and mature macrophages (R2s)
(Neumann et al., 1998, 2000).
2.7. Sorting of goldfish R1 progenitor cells from PKM cultures
previous studies in which all fish infected with this number of
parasites became infected (Bienek and Belosevic, 1997).
Freshly isolated cells from goldfish kidney, or cells from day 2
or day 6 PKM cultures were centrifuged at 230 × g for 10 min, enumerated using Trypan blue, and re-suspended to a concentration of
∼5–10 × 106 cells/mL in complete MGFL-15 medium containing 2%
penicillin/streptomycin for cell sorting on a FACS Aria flow cytometer at the Department of Medical Microbiology and Immunology,
University of Alberta, Flow Cytometry Facility. Cells were sorted
into tubes containing complete MGFL-15 medium containing 2%
penicillin/streptomycin.
2.4. Identification, cloning and sequencing of goldfish
transcription factors
2.8. Production and purification of recombinant goldfish kit
ligand A (rgkitla)
Primers were designed (IDT) using homology based PCR. Genbank accession numbers for the sequences used for homology
based PCR: Runx1 AF391125, cMyb NM 131266, GATA2 AB429308,
Egr1 NM 131248, CEBP␣ NM 131885, GATA1 BC164788, Lmo2
NM 131111, GATA3 AB302069, Pax5 AB429310. Partial sequences
for goldfish PU.1, cJun, and MafB were obtained from a differential
cross screen conducted in our lab previously (Barreda et al., 2004b).
The procedure for generation of amplicons, cloning, colony PCR,
and sequencing is described previously (Katzenback and Belosevic,
2009b). The 4peaks software (http://mekentosj.com/4peaks/) was
used to analyze the sequences. Quantitative PCR primers were
designed using the 7500 fast primer design software based on
the full or partial sequences of the goldfish transcription factors
obtained. The primers used for quantitative PCR and colony PCR
are listed in Table 1.
Recombinant goldfish kit ligand A (rgkitla) was cloned,
sequenced, expressed and purified as previously described
(Katzenback and Belosevic, 2009b). Briefly, rgkitla was produced by
creating a construct using the pSECTag2B vector (Invitrogen) and
transfected into HEK293T cells using TurboFect reagent (Fermentas). Transfected HEK293T cells were cultured at 37 ◦ C with 5% CO2 ,
and cell-conditioned medium containing the secreted recombinant
protein was collected every 3–4 days, cleared of suspension cells
by centrifugation at 230 × g for 10 min, and stored at 4 ◦ C until the
recombinant proteins were purified from cell-conditioned medium
using NiNTA beads.
2.5. Isolation of splenocytes and peripheral blood leukocytes
Spleens from individual goldfish (n = 4) were harvested and gently pushed through wire mesh screens to dissociate cells. Cells were
suspended in a homogenizing solution of MGFL-15 medium containing heparin to prevent clotting. Debris was allowed to settle out
before layering the spleen cell suspension onto 51% Percoll and centrifuged at 430 × g for 25 min. Cells at the interface were collected
and washed 2 times in MGLF-15 medium. To isolate peripheral
2.9. Production of recombinant goldfish colony stimulating
factor-1 (rgCSF-1)
Goldfish colony stimulating factor-1 (rgCSF-1) was amplified
using gene specific primers (IDT, Table 1), the amplicon was gel
purified using the QIA Gel Extraction Kita (Qiagen) and cloned
into the pCDNA3.1 mammalian expression vector (Invitrogen)
according to manufacturers protocols. Constructs were screened
by colony PCR using the vector specific primers T7 and BGH
(Table 1) and plasmid from positive colonies were isolated using
the QIA Miniprep Kit (Qiagen) and sequenced using an ET terminator cycle sequencing dye and run on a PE Applied Biosystems
377 automated sequencer. Sequences were analyzed using the
B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
4peaks software (http://mekentosj.com/4peaks/) for correct orientation and reading frame. The CSF-1 construct was transfected into
50–60% confluent CHO cells using Turbofect (Fermentas) according
to the manufacturers protocol. CHO cells were grown at 37 ◦ C in the
presence of 5% CO2 in complete DMEM (10% fetal bovine serum, 1%
sodium pyruvate, 1% non-essential amino acids, 15 mM HEPES, and
1% penicillin/streptomycin). The medium was collected every 5–6
days following transfection for 2–3 weeks, cleared of suspension
cells by centrifugation at 230 × g for 10 min, and stored at 4 ◦ C prior
to purification of secreted recombinant goldfish CSF-1 (rgCSF-1).
2.10. Purification of recombinant goldfish CSF-1 protein
CHO cell-conditioned supernatants were adjusted to 20 mM
imidazole and 100 mM HEPES, required for protein binding to
beads. MagneHis (Promega) beads were added to the adjusted
solution and incubated overnight at 4 ◦ C. MagneHis beads were
collected using the magnetic stand provided, and beads washed
5× with binding buffer (20 mM imidazole, 100 mM HEPES), followed by protein elution from the beads in 1 mL fractions using
the provided MagneHis elution buffer according to manufacturers
instructions. Buffer exchange from MagneHis elution buffer to 1X
PBS was performed using Zeba Spin Desalting Columns (Thermo
Scientific) according to specifications. The amount of protein was
determined using the Micro BCA Protein Assay Kit (Thermo Scientific) employing bovine serum albumin as the standard curve.
The solution containing rgCSF-1 was filter sterilized (0.22 ␮m) and
stored at 4 ◦ C until use.
2.11. Quantitative PCR of transcription factors of R1 cells isolated
from PKM cultures
R1 cells from day 0, day 2, or day 6 PKM cultures were sorted
as described above in Section 2.8. RNA was isolated using the
RNA MicroPrep Kit (ZymoResearch) and reverse transcribed into
cDNA using superscript II enzyme (Invitrogen) according to the
manufacturers protocol. Quantitative PCR for transcription factor
expressions was performed as described above in Section 2.5 and
primers are listed in Table 1 (n = 4). Values were normalized to the
R1 day 0 control for each transcription factor.
2.12. Treatment of goldfish R1 progenitor cells with recombinant
growth factors
Day 2 PKM cells were collected and R1 cells sorted. Cells were
washed 2× in MGFL-15, and re-suspended at a concentration of
3 × 105 cells/mL. To each well of a 6-well plate, 1 mL of cell suspension was added, followed by 1 mL of either medium, 200 ng/mL
of rgkitla, 200 ng/mL of rgCSF-1, or a combination of 200 ng/mL
of rgkitla and 200 ng/mL of rgCSF-1. This resulted in a final concentration of 100 ng/mL of rgkitla or 100 ng/mL of rgCSF-1. Cells
were harvested 6 h post treatment, RNA isolated using the RNA
MicroPrep Kit (ZymoResearch), reverse transcribed to cDNA using
superscript II enzyme (Invitrogen), and transcription factor expressions determined using the Applied Biosciences 7500 Fast Real Time
PCR machine. Values were normalized to the medium treated cells
(negative control) for all transcription factors (n = 4).
2.13. In vivo challenge of goldfish
Goldfish were injected i.p. with either PBS, 1 × 109 CFU of
heat-killed A. salmonicida A449, 1 × 108 T. carassii (3 dpi challenge
experiment), or 6.25 × 106 trypanosomes (7 dpi challenge experiment) in a volume of 100 ␮L. The 3 dpi or 7 dpi, goldfish were
sacrificed and kidneys and spleens harvested. Kidneys from fish at
3 dpi were dissociated as described above in Section 2.7, and R1 cells
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sorted as described in Section 2.8. Following cell sorting, R1s were
centrifuged at 230 × g for 15 min and medium aspirated. RNA was
isolated using the RNA MicroPrep Kit (ZymoResearch), and reverse
transcribed into cDNA using the superscript II enzyme (Invitrogen) according to the manufacturers specifications. For 7 dpi T.
carassii challenged goldfish, RNA was isolated from the kidney and
spleen tissue using Trizol (Invitrogen) and reverse transcribed into
cDNA using superscript II (Invitrogen) according to the manufacturers protocol. Quantitative PCR was performed using the Applied
BioSciences 7500 Fast Real Time PCR machine as stated above in
Section 2.5. Data were normalized for each transcription factor to
that of the PBS-injected controls (n = 4).
2.14. Statistics
Statistical analysis was performed using the delta Ct values for
all comparisons. Analysis of tissues (Fig. 1) and treatment of R1
progenitor cells with growth factors (Fig. 4) was performed using
a paired t-test, and analysis of cell populations (Fig. 2A–D) and R1
progenitor cells over time of culture (Fig. 3) was performed using
an ANOVA with a Dunnett’s multiple comparisons post hoc test in
which all treatments were compared to the control (R1 cells). For
all other figures an unpaired t-test was performed. A probability of
P < 0.05 was considered significant.
3. Results
3.1. Quantitative PCR mRNA levels of transcription factors in
goldfish kidney and spleen
The mRNA levels of the transcription factors Runx1, cMyb,
GATA2, PU.1, MafB, cJun, Egr1, CEBP␣, GATA1, Lmo2, GATA3 and
Pax5 in goldfish kidney and spleen tissues were analyzed by quantitative PCR. Transcription factors were grouped into four categories
based on their major involvement in lineage decisions. The first
group of markers of early progenitor cells consisted of the transcriptional regulators Runx1, cMyb, and GATA2. Expressions of these
transcription factors were observed in the kidney, however, only
runx1 and gata2 mRNA levels were detected in the spleen, while
cmyb mRNA levels were not detected (Fig. 1A).
The second group of the transcription factors were those
involved in the macrophage/granulocyte cell lineages. The transcriptional regulators comprising this group include PU.1, MafB,
cJun, Egr1, and CEBP␣. The cebp˛ mRNA levels were marginally
lower while cjun mRNA levels were marginally higher in the spleen
compared to that of the mRNA levels in the kidney (Fig. 1B). However, mRNA levels of pu.1, mafb, and egr1 did not significantly differ
between kidney and spleen tissues (Fig. 1B).
The third group of transcription factors was selected based
on their primary involvement in erythroid development-GATA1
and Lmo2. The gata1 mRNA expression was significantly higher
in the spleen compared to mRNA expression in the kidney, while
there was no difference in lmo2 mRNA expression between tissues
(Fig. 1C).
The last group of transcription factors were grouped together
based on their involvement in lymphopoiesis; GATA3 as a marker
of T-cell development and Pax5 as a master regulator of B-cell
development. Both gata3 and pax5 mRNA levels were significantly
and marginally higher in spleen compared to that of the kidney,
respectively (Fig. 1D).
3.2. Quantitative PCR mRNA levels of transcription factors in
goldfish cell populations
We next examined the expression of different transcription
factors in sorted R1 cells, peripheral blood leukocytes (PBLs),
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B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
Fig. 1. Quantitative PCR expression of goldfish transcription factors involved in early hematopoiesis (A), myelopoiesis (B), erythropoiesis (C), and lymphopoiesis (D) in
kidney and spleen tissues. Data was normalized to the kidney and standard error is shown. Significance is denoted by (*) compared to the reference sample (P < 0.05) marginal
significance (P < 0.08) is denoted by (§). ND, not detected (n = 4).
Fig. 2. Quantitative PCR expression of goldfish transcription factors involved in early hematopoiesis (A, E), myelopoiesis (B, F), erythropoiesis (C, G), and lymphopoiesis (D, H)
in R1 progenitor cells (R1s), peripheral blood leukocytes (PBLs), splenocytes and kidney tissue. Data was normalized to the R1 progenitor cells (A–D) or to kidney tissue (E–H)
and standard error is shown. Significance is denoted by (*) compared to the reference sample (P < 0.05) marginal significance (P < 0.08) is denoted by (§). ND, not detected
(n = 4).
and splenocytes. R1 cells from the kidney, the major hematopoietic organ of fish, consist of mainly progenitor cells. The runx1
mRNA expression was significantly lower in splenocytes compared to that of R1 cells, whereas the relative mRNA level of
runx1 in PBLs did not significantly differ from that in the R1
cells (Fig. 2A). Additionally, cmyb mRNA expression was significantly lower in PBLs and non-detectable in splenocytes compared
to cmyb mRNA expression in R1 cells (Fig. 2A). However, gata2
mRNA levels were significantly higher in both PBLs and splenocytes compared to those in the R1 cells (Fig. 2A). A similar trend
was observed for the other transcription factors involved in the
myeloid (Fig. 2B), erythroid (Fig. 2C), and lymphoid (Fig. 2D) path-
ways in which the relative expressions of transcription factors were
significantly higher in PBLs and splenocytes compared to the sorted
R1 cells.
3.3. Quantitative PCR mRNA levels of transcription factors in R1
cells in comparison to whole kidney tissue
To elucidate the cell types isolated from the kidney tissue that
compose the R1 progenitor cell population, we directly compared
the R1 cell population to that of the whole kidney tissue. The
transcription factors gata2, cjun and egr1 had significantly higher
mRNA levels in the R1 population of cells compared to those in the
B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
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Fig. 3. Quantitative PCR expression of goldfish transcription factors involved in early hematopoiesis (A), myelopoiesis (B), erythropoiesis (C), and lymphopoiesis (D) in sorted
R1 progenitor cells from day 0, day 2, and day 8 PKM cultures. Data was normalized to day 0 R1 progenitor cells for each transcription factor and standard error is shown.
Significance is denoted by (*) compared to the reference sample (P < 0.05) (n = 3).
kidney, while mRNA levels of cebp˛ and pu.1 were significantly
lower in R1 cells compared to the kidney (Fig. 2E and F). The mRNA
levels of pax5 and gata3, transcription factors involved in the lymphoid lineage, were also significantly higher in R1 cells compared
to those in the kidney tissue (Fig. 2H). The mRNA levels of lmo2
was significantly lower in R1 cells compared to the kidney tissue,
and a marginally significant up-regulation of gata1 mRNA levels
was observed in R1 progenitor cells compared to the kidney tissue
(Fig. 2G). As expected, this R1 cell population expressed markers
for HSCs/HPCs and lymphocytes.
3.4. Quantitative PCR mRNA levels of transcription factors in R1
cells isolated from PKM cultures
The kidney is the major hematopoietic organ of fish and we have
previously shown that the population of R1 progenitor cells isolated
from this organ, after cultivation for 4–10 days in the presence of
cell-conditioned medium (CCM) or rgCSF-1 results in the generation of monocytes and mature macrophages. Therefore, we wanted
to examine how the R1 cell population changes over time in culture as monocytes and macrophage are generated. R1 cells were
sorted at day 0, day 2, or day 6 of culture and the expression of the
different transcription factors normalized to that of the day 0 R1
cell population examined. The mRNA levels of the transcriptional
marker of early progenitor cells gata2 was significantly higher in
the day 2 R1 cells compared to that at day 0, and was significantly
lower in day 6 R1 cells compared to that in day 0 cells (Fig. 3A).
No significant differences were observed for cmyb or runx1 mRNA
levels at any time point (Fig. 3A).
The expression of mafb mRNA was significantly higher in day 2
R1 cells compared to day 0 cells by approximately 6-fold (Fig. 3B),
and was significantly lower by day 6 of cultivation compared to
day 0 R1 progenitor cells. While mRNA levels of cjun did not significantly differ in day 0 and day 2 R1 progenitor cells, mRNA levels of
this transcription factor were significantly lower in day 6 R1 progenitor cells compared to day 0 R1 cells. The transcription factor
mRNA levels of erythroid and lymphoid transcriptional regulators
exhibited a pattern of expression in which mRNA levels were significantly increased by day 2 of cultivation followed by a significant
decrease at day 6 of cultivation compared to day 0 progenitor cells
(Fig. 3C and D).
3.5. Effects of recombinant goldfish kitla and CSF-1 on
transcription factor expression in day 2 progenitor cells
Recombinant goldfish CSF-1 has previously been functionally
characterized and has been shown to be involved in the proliferation and differentiation of macrophages and their progenitors
(Hanington et al., 2007, 2009a), whereas rgkitla has been shown to
be involved in the survival of goldfish progenitor cells (Katzenback
and Belosevic, 2009a). We then examined whether these growth
factors are involved in the regulation of transcription factors associated with these functional processes. Therefore, to investigate
the effects of recombinant goldfish growth factors on transcription factor expression in progenitor cells in vitro, we treated day 2
progenitor cells with rgkitla, rgCSF-1, or rgkitla and rgCSF-1 in combination. Not surprisingly, we observed that many of the myeloid
and early progenitor transcription factors were modulated by these
growth factors. Treatment of day 2 progenitors with rgCSF-1 for 6 h
induced a significant up-regulation in the mRNA levels of the transcriptional regulators cjun, egr1, and cebp˛ (Fig. 4B). The expression
of transcription factors involved in early progenitor cells, erythropoiesis and lymphopoiesis were not significantly different from
medium treated controls (Fig. 4A, C and D).
Upon treatment of the day 2 progenitor cells with rgkitla, we
observed a significant up-regulation of the mRNA levels of mafb
and egr1 (Fig. 4B). Similar to treatment with rgCSF-1, there were
no significant differences between non-treated and rgkitla-treated
early progenitors when the mRNA levels of transcription factors
from the early progenitor cells, erythroid and lymphoid pathways
were measured (Fig. 4A, C and D). Previous studies examining the
function of kit ligand, also known as stem cell factor (SCF) in mammalian literature, found it to be synergistic with other cytokines.
Due to these observations, we also treated sorted day 2 progenitors with a combination of rgkitla and rgCSF-1. The mRNA levels
of the myeloid transcription factors egr1 and cebp˛ (Fig. 4B) were
significantly up regulated compared to time matched controls.
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Fig. 4. Real time PCR expression of goldfish transcription factors involved in early hematopoiesis (A), myelopoiesis (B), erythropoiesis (C), and lymphopoiesis (D) in sorted
day 2 R1 progenitor cells treated with recombinant growth factors. R1 progenitors were seeded at a concentration of 3 × 105 cells/mL and treated with medium (negative
control), 100 ng/mL of recombinant goldfish kit ligand a rg(kitla), colony stimulating factor 1 (rgCSF-1), or rgkitla and rgCSF-1 in combination for 6 h. Data was normalized
to the medium-treated R1 progenitor control cells for each transcription factor and standard error is shown. Significance is denoted by (*) compared to the reference sample
(P < 0.05) (n = 4).
3.6. Quantitative PCR mRNA levels of transcription factors in R1
progenitor cells isolated from heat-killed A. salmonicida A449
challenged goldfish
Due to the conserved nature of the transcription factors and
the pathways they are involved in, we decided to examine the
expression of transcription factors in vivo in order to assess the
early effects of natural fish pathogens on developing progenitor
cells. In our first set of experiments, we challenged goldfish with
1 × 109 heat-killed A. salmonicida or sham-injected PBS controls,
isolated R1 cells from the kidney 72 h post challenge and analyzed different transcription factor mRNA levels by quantitative
PCR. Following challenge with A. salmonicida, changes in the transcription factor mRNA levels were observed in the early progenitor
and myeloid groups, while no significant differences were observed
within the erythroid (Fig. 5C) or lymphoid (Fig. 5D) groups of transcription factors. Within the early progenitor group, a significant
down-regulation of runx1 mRNA levels and a marginally significant decrease in cmyb mRNA levels were observed in R1 cells
from heat-killed A. salmonicida challenged fish compared to PBSinjected control fish (Fig. 5A). In the myeloid group of transcription
factors, a significant increase in pu.1 and a marginal increase in
cjun mRNA levels were observed in R1 cells isolated from the heatkilled A. salmonicida exposed goldfish compared to the PBS-injected
controls. However, egr1 mRNA levels was significantly downregulated in the R1 cells from the A. salmonicida challenged group
(Fig. 5B).
3.7. Regulation of transcription factors in T. carassii infected
goldfish
The second pathogen we chose to examine was T. carassii, an
extracellular protozoan parasite of cyprinid fish. In the first set
of experiments, fish were injected with PBS (sham-injected control) or 1 × 108 trypanosomes and R1 cells from the kidney were
isolated 72 h post infection. The mRNA levels of the transcription
factors from the early progenitor group runx1, cmyb and gata2 were
significantly down-regulated in the sorted R1s from trypanosome
infected fish compared to the sorted R1s from the PBS-injected control fish (Fig. 6A). A similar trend was observed for the expression
of transcription factors in the myeloid, erythroid, and lymphoid
groups. The mRNA levels of the transcription factors mafb, egr1
and cebp˛ were all significantly down-regulated in R1s from fish
infected with T. carassii (Fig. 6B), while the mRNA expression of
pu.1 and cjun did not change. Furthermore, the mRNA levels of
gata1 (Fig. 6C), gata3 and pax5 (Fig. 6D) were significantly downregulated in R1 cells from T. carassii infected fish compared to
PBS-injected controls.
B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
1231
Fig. 5. Real time PCR expression of goldfish transcription factors involved in early hematopoiesis (A), myelopoiesis (B), erythropoiesis (C), and lymphopoiesis (D) in sorted
R1 progenitor cells from PBS injected or heat-killed A. salmonicida A449 challenged fish. Fish were injected with 1 × 109 CFU of heat-killed A. salmonicida A449 or an equal
volume of PBS (negative control). R1 progenitors were isolated from fish 72 h post challenge. Data was normalized to R1 progenitor cells from PBS injected fish for each
transcription factor and standard error is shown. Significance is denoted by (*) compared to the reference sample (P < 0.05) marginal significance (P < 0.08) is denoted by (§)
(n = 4).
In the second set of experiments, fish were injected with PBS
(sham injected controls) or infected with 6.25 × 106 trypanosomes
and kidney and spleen tissues isolated at 7 days post infection. We
chose a lower dose of parasites to infect fish with in this experiment compared to the first experiment as high numbers of parasites
within the host blood have been shown to cause host mortality.
After exposure to 6.25 × 106 trypanosomes, the parasites multiply within the host and reach peak parasitemia 2–3 weeks post
infection, followed by host recovery by 8 weeks post infection.
Therefore at 7 dpi, fish infected with 6.25 × 106 will have approximately the same parasite burden as those fish infected with 1 × 108
trypanosomes at 3 dpi.
In contrast to the first set of experiments, in which we observed
a generalized down-regulation in transcription factor mRNA levels in R1 cells isolated from trypanosome infected fish (Fig. 6),
the mRNA levels of the transcription factors in the kidney at 7 dpi
from T. carassii infected fish, except for runx1 mRNA levels which
was significantly down regulated in T. carassii infected fish, did not
significantly differ from the PBS-injected controls (Fig. 7A–D). However, when we examined the spleen for transcription factor mRNA
levels, there was a significant decrease in the expression of pu.1,
mafb and cjun (Fig. 8B) in T. carassii infected fish. No significant
differences were observed in the expression of erythroid (Fig. 8C)
or lymphoid (Fig. 8D) transcription factors. Although the relative
expressions of many of the transcription factors did not significantly differ between spleen tissue from PBS controls and T. carassii
infected fish, there was a general trend of down-regulation of the
expression of all transcription factors in the spleen of trypanosome
infected fish (Fig. 8).
4. Discussion
To increase our understanding of teleost HSCs/HPCs we chose
to use transcription factor mRNA levels as a tool to examine how
progenitor cell populations are influenced by growth factors and
in response to pathogens. cMyb is a marker of definitive HSCs in
developing zebrafish (Bertrand et al., 2008) and is required for
the production of all blood cells, suggesting an evolutionarily conserved role for cMyb in hematopoiesis (Soza-Ried et al., 2010).
In our study, we observed enhanced cmyb mRNA levels in the
kidney tissue and kidney R1 progenitor cells consistent with the
hematopoietic role of the kidney in teleosts, and suggest that the
R1 progenitor cell population most likely contains a population of
HSCs. This is in agreement with previous reports of isolation of a
side-population of cells believed to contain HSCs from adult ginbuna carp kidney (Kobayashi et al., 2006, 2007, 2008). Surprisingly,
cmyb expression in PBLs was observed, albeit at very low levels,
and may suggest the presence of a small fraction of circulating
HSCs in the blood of teleosts. Runx1 and GATA2 are also involved
in early hematopoiesis. Runx1 is well known for its role in the formation of HSCs (Swiers et al., 2010) and is expressed during T-cell
development, particularly in double-negative, double-positive, and
CD4+ and CD8+ T-cells (reviewed in Wong et al., 2011). The similar levels of runx1 in goldfish kidney and spleen tissues may be
due to the expression of this transcription factor in HSCs and Tcells, with the majority of HSCs being found in the kidney and a
population of T-cells contained within the spleen. GATA2, while
important for the survival and proliferation of multipotent progenitors, is broadly expressed amongst megakaryocytes and cells
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B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
Fig. 6. Real time PCR expression of goldfish transcription factors involved in early hematopoiesis (A), myelopoiesis (B), erythropoiesis (C), and lymphopoiesis (D) in sorted
R1 progenitor cells from PBS or T. carassii challenged fish. Fish were injected with 1 × 108 trypanosomes or an equal volume of PBS (negative control) and R1 progenitors
were isolated from fish 72 h post challenge. Data was normalized to R1 progenitor cells from PBS injected fish for each transcription factor and standard error is shown.
Significance is denoted by (*) compared to the reference sample (P < 0.05) (n = 4).
Fig. 7. Real time PCR expression of goldfish transcription factors involved in early hematopoiesis (A), myelopoiesis (B), erythropoiesis (C), and lymphopoiesis (D) in kidney
tissue from PBS (control) or T. carassii challenged fish. Fish were injected with 6.25 × 106 trypanosomes or an equal volume of PBS (negative control) and kidney tissue isolated
from fish 7 days post infection. Data was normalized to kidneys from PBS injected fish for each transcription factor and standard error is shown. Significance is denoted by
(*) compared to the reference sample (P < 0.05) (n = 4).
from the mast cell lineage (Tsai and Orkin, 1997). The highly significant increase in gata2 expression in PBLs and splenocytes compared
to R1 progenitor cells may be due to the presence of mast cells,
since GATA2 has recently been shown to be important in the devel-
opment of zebrafish mast cells (Dobson et al., 2008; Reite and
Evensen, 2006). Similarly, increased mRNA levels of the transcription factors cjun, egr1, gata1, gata3 and pax5 in the spleen most
likely reflect the expression of these transcription factors in mature
B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
1233
Fig. 8. Real time PCR expressions of goldfish transcription factors involved in early hematopoiesis (A), myelopoiesis (B), erythropoiesis (C), and lymphopoiesis (D) in spleen
tissue from PBS (control) or T. carassii challenged fish. Fish were injected with 6.25 × 106 trypanosomes or an equal volume of PBS (negative control) and spleen tissue isolated
from fish 7 days post infection. Data was normalized to spleens from PBS injected fish for each transcription factor and standard error is shown. Significance is denoted by
(*) compared to the reference sample (P < 0.05) (n = 4).
cells within the spleen, splenocytes and PBLs populations such
as monocytes/macrophages (Aude-Garcia et al., 2010; Krishnaraju
et al., 1998; Lord et al., 1993), erythrocytes, megakaryocytes, mast
cells (Kobayashi and Yamamoto, 2007), T-cells (Hosoya et al., 2010)
(Takizawa et al., 2008) and B-cells (Adams et al., 1992). Of particular
interest were the lower mRNA levels of cebp˛ in the spleen compared to those in the kidney. CEBP␣ is important for the production
of granulocytes, and we have previously isolated and characterized
a pool of neutrophil-like cells from the goldfish kidney (Katzenback
and Belosevic, 2009a). These results are consisting with our findings
of large numbers of neutrophils in the kidney, and further support
that the teleost kidney is the site of granulopoiesis.
Due to the importance of transcription factors at multiple junctures of developing immune cells and the development of multiple
cell lineages, we focused our efforts on the detailed examination
of the expression of transcription factors in the R1 progenitor cell
population during cultivation. R1 progenitor cells compared to
kidney tissue showed increased mRNA expressions of gata2 and
egr1, which have previously been identified as markers of HSCs
in humans, mice and zebrafish (Kobayashi et al., 2010), as well
as cjun, pax5 and gata3. These data suggest that our cultivation
system of PKM is enriching for a mixed population of the progenitor cells, most likely containing a small number of HSCs, myeloid
progenitors, and quite possibly a small population of lymphoid progenitors or mature lymphocytes. Furthermore, upon examination
of the R1 progenitor cell population over time in our culture system, we believe the dynamic changes in the expression of many of
the transcription factors involved in HSCs/HPCs, erythroid or lymphoid lineages may be due to the cell death that occurs by day 2
in our culture system (lag phase). MafB expression is important
in the self-renewal of progenitor cells (Aziz et al., 2009; Sarrazin
et al., 2009), and a decrease in MafB in progenitors results in an upregulation of PU.1 and in increase in cell responsiveness to CSF-1
(Sarrazin et al., 2009) to permit monocyte/macrophage differentiation which requires MafB expression (Aziz et al., 2009; Sarrazin
et al., 2009). Similarly, GATA2 is important for the maintenance and
proliferation of multipotent progenitor cells (Hosoya et al., 2010), as
well as inhibition of monocyte/macrophage differentiation by suppressing PU.1 (Maeda et al., 2010). Increased expression of mafb and
gata2 mRNA levels in day 2 R1 progenitors suggests that progenitor cell commitment to the macrophage lineage may be suppressed
at this time, and that this block to monocyte/macrophage differentiation is removed following day 2 of culture, coinciding with
the end of lag phase and the beginning of the proliferative phase
and macrophage outgrowth. Conversely, the up-regulation of mafb
mRNA levels in the R1 population may be occurring in a subpopulation of cells that is independent from the sub-populations
of cells expressing gata2 mRNA, which suggests that commitment
of progenitors to a macrophage lineage may occur at day 2 of
cultivation.
Treatment of progenitor cells with rgCSF-1 showed upregulation of myeloid transcription factor mRNA levels cjun and
egr1, known to be involved in the differentiation of myeloid progenitors into monocytes/macrophages (Cai et al., 2008; Loose et al.,
2007; Nguyen et al., 1993). Possibly, the endogenous production
of CSF-1 by alternative macrophages present early in PKM cultures (Barreda et al., 2000; Neumann et al., 1998) may signal for
the commitment, proliferation and differentiation of the day 2 R1
progenitor cells, thereby ending the lag phase and signaling the
entrance into the proliferative phase of PKM cultures (Barreda et al.,
2000). The mixture of endogenous growth factors produced by the
PKM cells is complex. Thus far we have identified and functionally
characterized the following growth promoting and differentiation
factors: CSF-1, LIF, granulin and kitla (Hanington and Belosevic,
2007; Hanington et al., 2007, 2008; Katzenback and Belosevic,
2009b). Since kit ligand is known to act during early hematopoiesis,
we assessed whether it affected the expression of the transcription factors in progenitor cells. The observed increase in mafb and
egr1expressions support the functional role of rgkitla as a promoter
of progenitor cell survival (Katzenback and Belosevic, 2009b), as
Erg1 is known to influence the maintenance of HSCs quiescence and
location within the bone marrow niche (DeLigio and Zorio, 2009).
The up-regulation of cebp˛ mRNA in response to treatment with
rgkitla suggests that rgkitla may be involved in fish mast cell development similar to the mammalian system (Ashman, 1999). The
treatment of progenitor cells with the combination of growth factors maintained the up-regulation in the expression of the myeloid
transcription factors egr1 and cebp˛ and suggests that rgkitla and
rgCSF-1 may synergize to induce differentiation along the monocyte/macrophage lineage. The possible functional synergy between
rgkitla and rgCSF-1 is currently under investigation in our laboratory.
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B.A. Katzenback et al. / Molecular Immunology 48 (2011) 1224–1235
We then examined how the HSC/HPC pool was regulated
in vivo in response to pathogens. The regulation of the transcription factor mRNA levels in R1 progenitors isolated from
heat-killed A. salmonicida challenged fish suggests a shift towards
early myeloid committed progenitors. However, down-regulation
of runx1 and egr1 mRNA levels may suggest an arrest in
commitment/progression of these progenitors to the monocyte/macrophage lineage, or possibly the mobilization of these cells
from the hematopoietic organ to the periphery. Similar observations were reported for Listeria monocytogenes infection of mice,
where there was a decrease of myeloid precursors from days 1 to 4
post infection. However, as the infection progressed, the numbers
of myeloid progenitors recovered and there was an enhancement
of monopoiesis at the expense of other cell lineages (Serbina et al.,
2009). The progenitor cells from T. carassii infected fish showed
different expression profiles of transcription factors. The generalized down-regulation of transcription factor expression may
be explained by the immunosuppressive environment that trypanosomes are known to induce, as well as the added demand
on the hematopoietic system to replace dying cells. Similar observations have been reported for other pathogen/host systems. For
example, immunosuppression in mice caused by T. brucei infection
was related to significant (50%) reduction in the nucleated cells
from the bone marrow following peak parasitemia, and the capacity
of equal numbers of these cells to form spleen-colony-forming units
was diminished by more than 50% (Clayton et al., 1980). A decrease
in the number and colony forming unit potential of myeloid and
erythroid progenitors was also seen in cytomegalovirus infected
BALB/c mice (Gibbons et al., 1995). However, by 7 days post infection the only significant down-regulation was in runx1 mRNA levels
in the kidney tissue from T. carassii infected fish. This may suggest
that after pathogenic insult the recovery and return to homeostasis
in the goldfish kidney is relatively rapid. In the spleen of infected
fish, a general trend in down-regulation of transcription factor
mRNA levels may suggest a lack of mature cells present in this
tissue.
Despite the lack of available reagents to examine teleost progenitor cells, we have employed the conserved nature of transcription
factors as a tool to gain a better understanding of this important population of cells. By quantifying the expression of different
transcription factors under different conditions, we examined the
dynamics of the sorted progenitor cell populations in our unique
PKM cultivation system and how growth factors influence these
cells. Our results provide a basis for using the transcription factor
expression as a marker for development and differentiation status
of myeloid cells. Furthermore, while many studies have examined
how mature immune cells respond to pathogens, we have yet to
systematically examine how pathogens are able to modulate the
progenitor cell pools in the kidney of the bony fish. Our results
indicate that there is significant modulation of HSCs/HPCs during
“emergency” conditions in the teleost kidney. Whether this modulation is directly influenced by pathogen molecules or is a result of
generalized increase in the hematopoietic demand remains to be
elucidated.
Acknowledgements
This research was supported by a grant from the Natural Sciences and Engineering Research Council of Canada (NSERC) to MB
and by NSERC and AIF doctoral scholarships to BAK. We thank
Dr. Allen Shostak for help with statistical analyses, Ayoola Oladiran for providing tissue cDNA samples from trypanosome infected
fish, and Dorothy Kratochwil-Otto from the Department of Medical Microbiology and Immunology Flow Cytometry Facility at the
University of Alberta for technical assistance in cell sorting.
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