edwardsiella ictaluri is capable of persisting in channel
TRANSCRIPT
Louisiana State University Louisiana State University
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LSU Doctoral Dissertations Graduate School
7-8-2020
Edwardsiella Ictaluri Is Capable of Persisting in Channel Catfish Edwardsiella Ictaluri Is Capable of Persisting in Channel Catfish
by Evading Host T Cell and Cell Death Responses by Evading Host T Cell and Cell Death Responses
Elizabeth Watts Griggs Louisiana State University and Agricultural and Mechanical College
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EDWARDSIELLA ICTALURI IS CAPABLE OF PERSISTING IN
CHANNEL CATFISH BY EVADING HOST T CELL AND CELL
DEATH RESPONSES
A Dissertation
Submitted to the Graduate Faculty of the
Louisiana State University and
Agricultural and Mechanical College
in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
in
Department of Pathobiological Sciences
by
Elizabeth Griggs
B.S., Louisiana Tech University, 2011
M.S., Louisiana Tech University, 2013
August 2020
ii
ACKNOWLEDGMENTS
During my journey through this program I have received assistance and support from a
number of persons; members of the faculty, other students both past and present, friends, and
members of my family; and I would like to pause to recognize them for their contributions of
help and guidance along the way.
I would like to acknowledge Dr. Ronald Thune for his guidance and support throughout
this entire process, and who was always there to mentor and advise me during times of difficulty
as well as the times when everything went smoothly.
I would like to acknowledge Dr. Rebecca Giorno-McConnell who lit the spark of
microbiology in me and encouraged me to pursue it as a career; and who became my advisor for
my master’s program. Had I never encountered her, I would never have pursued this degree.
I’d also like to thank current and past members of the Thune lab, Doctors Christine
Darnall, Chanida Fongsaran, Lydia Dubytska, and Carolyn Chang, as well as other members of
the Department of Pathobiological Sciences, in particular Thaya, Marilyn, Trina and Jennifer.
I also seriously appreciate the care and patience of my parents and extended family who
have been constant sources of comfort throughout my life, and through this process.
I would be remiss if I did not also acknowledge my God and Creator, who has always
been with me and has led me to where I am today, and who allows my path to unfold according
to his will.
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TABLE OF CONTENTS
ACKNOWLEDGMENTS .............................................................................................................. II
LIST OF TABLES .......................................................................................................................... V
LIST OF FIGURES ...................................................................................................................... VI
ABSTRACT ................................................................................................................................ VIII
CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW ................................................1 Catfish Aquaculture ......................................................................................................................1 Edwardsiella Taxonomy ..............................................................................................................2 Edwardsiella ictaluri: Mechanisms of Pathogenesis ...................................................................9
Edwardsiella ictaluri Secretion Systems ...................................................................................12 Type III secretion systems and Edwardsiella ictaluri ................................................................13
Objectives and Hypotheses ........................................................................................................18 Literature Cited ..........................................................................................................................19
CHAPTER 2. ESEK HOST INTERACTION AND PROTECTIVE ABILITY AGAINST
SUBSEQUENT WILD-TYPE EXPOSURE .................................................................................28 Introduction ................................................................................................................................28
Materials and Methods ...............................................................................................................31 Results ........................................................................................................................................37
Discussion ..................................................................................................................................45 Literature Cited ..........................................................................................................................47
CHAPTER 3. NAÏVE HEAD KIDNEY DERIVED MACROPHAGES FAVOR M1
POLARIZATION IN RESPONSE TO EDWARDSIELLA ICTALURI INFECTION ...................51 Introduction ................................................................................................................................51
Methods ......................................................................................................................................53 Results ........................................................................................................................................55
Discussion ..................................................................................................................................60 Literature Cited ..........................................................................................................................73
CHAPTER 4. EDWARDSIALLA ICTALURI EVADES T CELL RESPONSES IN THE
CHANNEL CATFISH ...................................................................................................................78 Introduction ................................................................................................................................78 Methods ......................................................................................................................................80
Results ........................................................................................................................................85
Discussion ..................................................................................................................................91 Literature Cited ..........................................................................................................................98
CHAPTER 5. GENERAL CONCLUSIONS ...............................................................................105 Literature Cited ........................................................................................................................110
APPENDIX I: ABBREVIATIONS COMMONLY USED IN THIS DISSERTATION ............112
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APPENDIX II: CHAPTER 1 SUPPLEMENTAL MATERIAL .................................................114
APPENDIX II: CHAPTER 4 SUPPLEMENTAL MATERIAL .................................................120
APPENDIX III: FAILED AND ONGOING EXPERIMENTS...................................................123
LIST OF REFERENCES .............................................................................................................126
VITA ............................................................................................................................................146
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LIST OF TABLES
Table 1.1 Biochemical testing results of Edwardsiella species. .....................................................5
Table 2.1: Strains and plasmids utilized in the scope of this research project. ..............................32
Table 2.2: Primer sets. ...................................................................................................................33
Table 2.3: Safety of ΔeseK vaccinated fish....................................................................................42
Table 3.1: Top 50 reads via GSA...................................................................................................57
Table 3.2 Top upregulated pathways Predicted by IPA showing the top predicted genes per
pathway. .........................................................................................................................................61
Table 3.3 Top Downregulated Pathways predicted by IPA showing the top predicted genes per
pathway. .........................................................................................................................................67
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LIST OF FIGURES
Figure 1.1: T3SS of E. ictaluri Modified from Pallen et al ...........................................................14
Figure 2.1: Phyre 2 Model of EseK ...............................................................................................30
Figure 2.2: EseK::3XFLAG Confirmation ....................................................................................38
Figure 2.3: SYPRO Ruby Red Stain of Co-IP ...............................................................................39
Figure 2.4: Positional hits from mass spectrometry tryptic digest of proteins excised from bands
after Co-IP ......................................................................................................................................40
Figure 2.5: Preliminary Vaccination and Challenge ......................................................................41
Figure 2.6: Early Exposure to WT .................................................................................................44
Figure 2.7: Late WT challenge. .....................................................................................................45
Figure 3.1: Top 40 pathways according to overall -log(p-value) (y- axis), differentially regulated
in WT compared to uninfected HKDMs ........................................................................................59
Figure 3.2: Combined NF-κB virus and P13K/AKT signaling pathway .......................................66
Figure 3.3: Death Receptor signaling pathway ..............................................................................69
Figure 4.1: Representation of gating strategy with Day 0 samples ...............................................84
Figure 4.2: CD74 and MIF expression in HK per treatment graphed by the log2 transformation of
normalized RNA counts per day ....................................................................................................85
Figure 4.3: Expression of T cell Markers in HK per treatment graphed by the log2 transformation
of normalized RNA counts per day ...............................................................................................87
Figure 4.4: Expression of other cytokine indicators in HK per treatment graphed by the log2
transformation of normalized RNA counts per day .......................................................................88
Figure 4.5: CD74 and MIF expression in PBL per treatment graphed by the log2 transformation
of normalized RNA counts per day.. .............................................................................................89
Figure 4.6: Expression of T cell markers in PBL per treatment graphed by the log2
transformation of normalized RNA counts per day .......................................................................90
Figure 4.7: Expression of other cytokine indicators in PBL per treatment graphed by the log2
transformation of normalized RNA counts per day .......................................................................92
Figure 4.8: Percentage of CD3e+ lymphocytes grouped by treatment with SEM.........................93
vii
Figure 5.1 Macrophage and T cell activation ..............................................................................109
viii
ABSTRACT
Edwardsiella ictaluri is a gram-negative bacterium of the family Enterobacteriaceae that
infects and causes enteric septicemia (ESC) of channel catfish (Ictalurus punctatus), a fatal
disease costing the catfish industry millions of dollars in losses each year. Edwardsiella. ictaluri
is capable of replicating in catfish head-kidney-derived-macrophages (HKDM), and like many
other gram-negative bacteria, E. ictaluri encodes a Type III Secretion System (T3SS) that is
required for virulence and intracellular replication. In the case of E. ictaluri, the T3SS
translocates effectors from the Edwardsiella containing vacuole (ECV) through the bacterial cell
wall and the vacuolar membrane directly to the host cytoplasm. Of the nine known effectors, this
work analyzed one effector, EseK to determine the potential for cell-mediated immune (CMI)
responses in naïve fish and the fate of non-activated head-kidney-derived macrophages
(HKDMs) in response to infection. We determined that the binding partner of EseK is CD74, and
an EseK knockout strain provides catfish fingerlings with protection against subsequent WT
exposure. RNA sequencing using infected and uninfected HKDMs uncovered strong indications
for the M1 phenotype in response to infection. This data also indicates that E. ictaluri evades
typical programed-cell death measures, and suppresses the CD40 pathway, which is critical for T
cell dependent activation. Finally, in vivo immune responses detected several regulation
differences, notably downregulation of CD40L in infected catfish, further implicating the loss of
this pathway due to infection. Within the scope of this work, we did not discover any specific
differences in immune regulation that could be attributed to EseK, but this research supports the
theory that E. ictaluri modifies the macrophage environment in order to persist and replicate in
the host, and E. ictaluri evades CMI responses further aiding its survival in the host.
1
CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW
Catfish Aquaculture
Worldwide demand for sustainable seafood products is increasing, and to meet that
demand, reports indicate that global aquaculture production will need to increase by 36.7% by
2030, and 11% in the United States (1). In 2017, the value of United States aquaculture
production was approximately $1.2 billion USD, and the leading contributor to aquaculture
production is the channel catfish, Ictalurus punctatus (2). Catfish production typically accounts
for 1/3 to almost 1/2 of the total United States aquaculture production, but is currently on the
decline (2). For example, in 2008, catfish aquaculture was worth $390 million USD, 39.6% of
the total U.S. aquaculture production, but in 2017 catfish production was valued at
approximately $355 million USD, accounting for 29.2% of the total United States aquaculture
(2). The focus of this dissertation is on one culprit behind this decline, the gram-negative
bacterial pathogen Edwardsiella ictaluri. But before we focus on E. ictaluri, an understanding of
basic catfish farming practices is necessary.
Catfish farming began in the United States in the 1950s, and rapidly expanded in the
1960s, as the ability to properly rear and care for catfish was developed (3). Catfish farms can be
found across the U.S. but are most predominant in the southeastern states of Louisiana,
Arkansas, Alabama, and Mississippi (4). Catfish farms typically use channel catfish because they
provide one of the best dress out and feed conversion ratios , but also use other species such as
blue catfish Ictalurus furcatus (3). Farmers typically move fish three times during the catfish
rearing process. First, the farmers move eggs from spawning cans in the broodfish ponds to the
hatchery, then about 7-10 days post-hatch, move fry to fingerling ponds, and finally, move
2
fingerlings to grow-out ponds where they will remain 18 months to 2 years until the fish reach
approximately 1.5 pounds each (3).
The catfish industry faces many challenges to production, including competition with
imported catfish species, such as basa (Pangasius bocourti) and swai/tra (Pangasius
hypopthalmus), and other imported fish species, increases in feed prices, and diseases, including
columnaris, channel catfish virus (CCV), and enteric septicemia of catfish (ESC) (4, 5). The
latter of these ESC, caused by the bacterium Edwardsiella ictaluri, is the focus of this work.
Several Edwardsiella species can infect channel catfish, but E. ictaluri, is still the most
prevalent (6). Enteric septicemia of catfish was first described from diseased catfish reared in
ponds in 1979 and is a continuous source of loss to catfish production (5, 7, 8). As of 2010,
catfish operations reported ESC outbreaks on 19.3% of fry/fingerling operations, 40.4% of
fingerling operations, and 36.6% of operations producing food size fish (5). It is important to
note that factors affecting these statistics include: the use of more resistant hybrid fish,
underreporting/not diagnosing infected fish, taking infected fish off feed, and in some rare cases,
on about 3% of reporting operations, vaccination (5). Given this information and the need to
sustain or increase catfish production in the coming years, it would be wise to increase our
understanding of ESC, a disease that still wreaks havoc in the industry. A better understanding
of E. ictaluri should lead to improved prevention and control methods to help this valuable
industry.
Edwardsiella Taxonomy
Edwardsiella tarda, first identified in 1965, was the first species of the genus
Edwardsiella described and initially was the lone species in the genus (9). As early as 1959,
several groups studying unknown cultures known as ‘bacterium 1483-59’ found that these
3
cultures did not match anything known in the literature (9). Through diagnostics, researchers
determined that this organism belonged to the family Enterobacteriaceae, but was different from
the previously classified genus and species of this group because the IMViC, a four-part test
specific for identifying organisms of the coliform group, and additional tests showed 20 points of
difference from Escherichia coli, including production of hydrogen sulfide. This data supported
the description of a new genus, Edwardsiella, and the first species, Edwardsiella tarda (9).
Phenotypic traits of E. tarda can be found in Table 1.1, but based on the original analysis, major
traits of E. tarda are that it is gram-negative, rod-shaped, β-hemolytic, ferments glucose, and
reduces nitrate to nitrite (9).
Through the early 2000’s E. tarda was isolated from fresh and brackish water
environments, as well as from healthy and diseased animals in and connected to these
environments. Affected animals include fish, reptiles, and humans, and was described as the
cause of emphysematous putrefactive disease (EPDC) in catfish (10), red disease in eels (11),
and gastroenteritis in humans (12-14). However, as of 2009, EPDC, now often called
Edwardsiellosis (15), has been described in a variety of fish, including the Japanese flounder, red
sea bream, Japanese eel, ayu, and Nile tilapia (cited by)(16).
For a little over a decade, E. tarda was the only species in the genus until the description
of Edwardsiella hoshinae and Edwardsiella ictaluri in 1980 and 1981, respectively (17, 18).
Because it was able to produce acid from mannitol, sucrose, trehalose, and salicin, and was able
to utilize malonate (Table 1.1) E. hoshinae was determined to be a different species from E.
tarda (the typical strain) (17). Birds, reptiles (17), and in some cases, humans (13) can carry E.
hoshinae. Unfortunately, there are only a handful of E. hoshinae papers in the literature because
it is not associated with major pathogenesis in any of the described hosts.
4
Researchers, in a 1981 paper, identified a new species of Edwardsiella, E. ictaluri that infects
channel catfish (Ictalurus punctatus), although evidence suggests its presence as early as 1969
in the southeastern United States (7, 18). The defining differences of E. ictaluri from E. tarda
are: it is α-hemolytic, does not grow at higher temperatures of 30 and 40C, is less resistant to
NaCl, is indole negative, and cannot produce H2S on TSI slants (Table 1.1) (18). Since the
discovery of E. ictaluri, the list of susceptible fish expanded to include tilapia, zebrafish, barbs,
green knife fish and other catfish species; but channel catfish remains the most relevant
susceptible species to E. ictaluri infection. E. ictaluri does not infect non-fish species (7, 19).
The geographical range of E. ictaluri includes the United States (7), Vietnam (20), Thailand (21),
Indonesia (22), Turkey (23), and Japan (16, 24) (tilapia isolates of Soto, Western hemisphere
Caribbean?). An in-depth review of this pathogen will follow this section, but briefly, E. ictaluri
invades the host via several potential entry points: orally and through the gills, nares, and skin
abrasions (7). The transmission is primarily fecal/oral and after ingestion it subsequently
breaches the epithelial barrier in the intestine, where it gains entry to the bloodstream and
disseminates throughout the rest of the body (25-27).
For over 30 years, the Edwardsiella genus only contained these three species, although
tests suggest considerable variability in E. tarda strains (28, 29). The evolution of procedures
used to characterize Edwardsiella species and strains and the naming systems commonly used in
the literature to discuss E. tarda has led to the current nomenclature. Previous methods
commonly used, such as SNPs in the gyrB gene, a combination of differences in antibiotic
susceptibility, generally consistent differences in the two plasmids carried by E. ictaluri, and the
presence or absence of particular genes, such as an absence of esrC in most zebrafish isolates,
and absence of eseI, escD, and virD4 from tilapia and zebrafish allowed for better
5
Table 1.1 Biochemical testing results of Edwardsiella species. Table modified primarily from
Ucko et al (44). Legend as retrieved from Ucko et al and Abayneh et al. : Fg, ferments glucose;
+d, delayed reaction; nd, not determined; [-], negative 75 to 89% of the time.
E. tarda
E.
hoshinaea
E.
ictaluri
E.
piscicida
E.
anguillarum
E.
piscicida-
like
Type Strain
Bacterium
1483-59 CIP 78.56
GA 77-
52 ET883 ET080813T
EA18101
1
Naming
Source
Ewing
1965
Grimont
1980
Hawke
1981
Abayneh
2013 Shao 2015
Ucko
2016
Traits
Gram stain - - - - - -
sMorphology Rod Rod Rod Rod Rod Rod
Red blood cell
hemolysis Beta nd Alpha Beta nd Gamma
Motility + nd
at 25°C + + + -
at 37°C + - + -
OF glucose Fg nd Fg Fg nd Fg
Growth at
20oC + nd + + nd +
25oC + nd + + nd +
30oC + nd - + + +
40oC + nd - + + (37-42oC) +
Growth in
NaCl
1% + nd + + + +
2% + nd - + + +
3% + nd - + + +
API20E
Arginine - - - - - -
Lysine + + + + + +
Ornithine + + + + + -
Citrate
(Simmons') - - - - + +
H2S on TSI + + - + + +
Urease - nd - - - -
Phenylalanine - nd - - nd nd
Indole + [-] - + + -
Gelatin - nd - - - -
Glucose + nd + + + +
Mannitol - + - - + +d
Inositol - nd - - - -
(table cont’d)
6
Table 1.1 continued
E. tarda
E.
hoshinaea
E.
ictaluri
E.
piscicida
E.
anguillarum
E.
piscicida-
like
Sorbitol - - - - - -
Rhamnose - - - - - -
Melebiose - - - - - -
Arabinose - [-] - - + -
cytochrome
oxidase
(CyOx) - - - - - -
Metabolism
and others
Lactose - - - - - -
Sucrose - + - - - -
Maltose + nd + + + +d
Xylose - nd - - nd -
Trehalose - + - - - -
Cellobiose - nd - - nd -
Erythritol - nd - - nd nd
Dulcitol - nd - - nd -
Salicin - [+] - - nd -
Adonitol - nd - - nd -
Malonate - + - - nd -
Galactose + nd + + + +
Mannose + nd + + - +
Nitrate
reduction to
nitrite + nd + + nd +
o-
Nitrophenyl-
b-D -
galactosidase
(ONPG) - nd - - nd -
Methyl red
test + + + + + nd
Voges-
Proskauer
(VP) - nd - - + - a Abayneh 2013 was used in addition to Grimont 1980 to provide more biochemical testing
results for E. hoshinae.
7
differentiation of E. ictaluri strains from different fish species (30). Unfortunately, many of these
tests are also limited for in depth categorization of Edwardsiella species and strains (30). For
instance, one group used multiplexed PCR to identify major fish pathogens including
Flavobacterium columnare, E. ictaluri, and Aeromonas hydrophila (31). Unfortunately, E.
ictaluri 16S rDNA, the target, evolved slowly (30), making it implausible to use to detect
divergence between the Edwardsiella species E. tarda and E. ictaluri (32).
Advances in diagnostics have led to a better differentiation of E. tarda. Some researchers,
have detailed the history and utilized various identification methods in the ongoing quest to
better characterize Edwardsiella strains, with particular attention given to E. tarda (32, 33). This
effort led to the use of an important method for differentiation, Multi-Locus Sequence Analysis
(MLSA) (32-34). Ultimately, using MLSA, targeting several genes including gyrB, mdh, adK,
and metG, led to the conclusion that many E. tarda isolates from fish were misclassified (32).
Three commonly used strategies exist for differentiating strains of E. tarda. First, at the
inception of the genus naming, serovar/serotyping to differentiate strains found 21 serotypes
based on a preliminary investigation of 37, strains including those from O and H antigen groups
(9). Also, using this system on 445 isolates from eels, water, and sediments, divided E. tarda
strains into four different serotypes, A, B, C, and D using LPS O-antigen (35). Another group
characterized 61 O groups and 45 H antigens, and suggested this strategy for international
application (36).
Another grouping system relied on phenotypic characteristics that led to the identification
of typical versus atypical E. tarda strains. Typical E. tarda strains are motile, usually come from
freshwater sources, and in experiments testing virulence against three species, yellowtail,
Japanese flounder, and red sea bream, is virulent in the first 2 species, but not red sea bream (37,
8
38). Atypical E. tarda strains are nonmotile, usually come from marine isolates, and in a study
testing virulence against three species, yellowtail, Japanese flounder, and red sea bream, were
virulent in all three (37, 38). There are also some genetic differences between these two groups.
MLSA has revealed a genetic diversity among E. tarda isolates from different host and
geographical regions, and pointed out a split between E. tarda groups with the fish isolates
grouping more closely with E. ictaluri as a separate species leading to a suggestion that E. tarda
is actually comprised of multiple species (32). Further expansion on this theory using MLSA in
combination with repetitive element sequence-based PCR (rep-PCR) identified two distinct E.
tarda groups called DNA group I, and DNA group II (33). This grouping is supported by similar
findings from other investigators (28, 39-42). It was proposed that DNA group I evolved first,
and that DNA group II and E. ictaluri evolved later, and gave further support to a new species
previously hidden within the E. tarda species (33). Data presented by Griffin et al. also
suggested that the typical and atypical strains previously reported by Sakai et al. both fall into
DNA group II , which is more closely related to E. ictaluri (16, 33). This ultimately led to the
rapid identification of two new Edwardsiella species, E. piscicida, type strain ET883, and E.
anguillarum, type strain ET080813T (32, 33).
Phenotypically E. piscicida is highly similar to E. tarda (Table 1.1). Researchers
reclassified E. tarda strains using species-specific gyrB primer sets for E. piscicida, leading to
the observation that E. piscicida has increased prevalence as a catfish pathogen compared to E.
tarda (6).
Additionally, recently identified E. anguillarum, (identified from eel isolates) is distinctly
different from E. tarda and E. piscicida (43). Biochemically, E. anguillarum differentiates from
E. tarda and other Edwardsiella species because it is citrate and arabinose positive (Table 1.1).
9
E. anguillarum also has 3 Type VI Secretion Systems (T6SS) and 2 Type III Secretion Systems
(T3SS); with the T6SS1 and T3SS2 highly conserved among E. anguillarum, piscicida, and
ictaluri. The T6SS2, T6SS3 and T3SS1 however, are unique to E. anguillarum (43). The T3SS1
is also similar to the Locus of Enterocyte Effacement (LEE) of E. coli, and T6SS1 and T6SS2
are similar to Pantoea ananatis and may be involved in lateral gene transfer (43).
There is also one additional, yet to be named species that is E. piscicida-like, type strain
EA181011 that is also highly similar to E. piscicida but is indole negative and gamma hemolytic
(44). With more of the narrative coming together, a recent study identified genes that can be
specific to differentiating between the five named strains, in particular, dnaJ, aiding the
reclassification of several E. tarda isolates as E. piscicida and E. anguillarum (45).
Edwardsiella ictaluri: Mechanisms of Pathogenesis
E. ictaluri is pathogenic to catfish and several other fish species. It typically presents as
an acute gastrointestinal enteritis which progresses into septicemia often associated with high
mortality. It can also appear, often in fingerling fish, as a chronic “hole-in-the-head” lesion
which is a result of meningoencephalitis (46-48). Catfish populations are at the greatest risk for
ESC in the spring and fall months when the water temperature is moderate and in the range of 22
to 28°C (49). This is the so called “ESC window”. This bacterium can survive several days in
water, and has been shown to be capable of surviving up to 95 days in sterile pond mud (48, 50).
Fish can be visually identified as infected with ESC by observing behavioral changes, including
swimming in circles or with the head up and tail down, or by not eating (7). Gross clinical signs
include: skin ulcerations, petechial hemorrhages in the skin, muscle, intestine, and fat tissues; a
swollen abdomen indicative of fluid accumulation in the body cavity; and/or mottled areas in the
liver indicative of necrotic foci (7).
10
As stated previously, the general route of entry of E. ictaluri is oral, but may be also via
the gills, and nares (7). Once E. ictaluri is ingested it migrates to the intestine and invades
through the epithelial lining and disseminates through the bloodstream (25, 26). Other
experiments have shown that water borne exposure can lead to invasion of the olfactory sac
followed by damage to the epithelium and inflammation of the olfactory sacs, and ultimately
entry to the brain from the olfactory bulb and dissemination resulting in meningoencephalitis
(25, 47, 48, 51). Experiments have suggested that uptake and dissemination can occur quickly.
One experiment infecting fish by gastric intubation was able to detect E. ictaluri in kidney
samples 15 minutes post infection and in liver samples 30 minutes post infection (52). This
group also showed that after infection, E. ictaluri can be detected along the intestinal brush
border at 30 minutes post infection, with phagocytic cells present near the basement membrane
(53). Twenty-four hours after fish are exposed to E. ictaluri, infiltration of mononuclear cells can
be observed in the intestine (47, 51). Other tissues affected by E. ictaluri include the skin,
muscle, spleen, intestine, and brain (54). Fish that survive an outbreak have the potential to carry
E. ictaluri up to 200 days (7).
E. ictaluri is internalizes in several cells, including the channel catfish ovary cell line
(CCO), neutrophils, and macrophages (55, 56). Head kidney derived macrophages (HKDM) are
used in many experimental assays to obtain a better understanding of pathogenesis in this cell
type. E. ictaluri can infiltrate, survive, and replicate in catfish HKDM (57). While Booth et al.
speculated that E. ictaluri likely has some ligands or receptors involved in uptake into
macrophages, they showed that opsonization of live E. ictaluri with normal catfish serum greatly
increases E. ictaluri’s uptake into catfish macrophages (57). Additionally, they found that E.
ictaluri replicates in spacious vacuoles within the macrophage similar to S. typhimurium in
11
Salmonella containing vacuoles SCV’s, leading to the naming of Edwardsiella containing
vacuoles (ECV) (57).
The ECV initially acidifies the vacuolar environment to a pH of 4, 30 to 210 minutes post
infection, a process that is dependent on the vacuolar H+ -ATPases of the HKDM (58). While E.
ictaluri survives well at low pH, it cannot replicate at pH lower than 6, but with the addition of
exogenous urea in the media, E. ictaluri increases the pH to a neutral condition favorable for
replication (59).
E. ictaluri is considered urease negative, biochemically, but it was found to have a
pathogenicity island containing nine urease associated genes, including an acid activated urease
enzyme similar to the Y. enterocolitica class of ureases (59). The typical function of a bacterial
urease is to hydrolyze urea to ammonia and carbamate. The carbamate then breaks down to
carbonic acid and more ammonia in solution, which ultimately gives rise to ammonium and an
increase in pH as the reaction comes to equilibrium (60). Macrophage-encoded arginase is the
source of urea, which modulates the supply of arginine and regulates iNOS and NO production
(61, 62). Arginase degradation of arginine in favor of production of urea may promote E.
ictaluri’s resistance to killing in HKDM by reducing substrates available for NO production, and
simultaneously provide urea for ammonia production by urease, which aids E. ictaluri’s ability
to modify pH regulation (59). This allows E. ictaluri to modulate the low pH environment in the
HKDM vacuoles and possibly the GI tract (63).
E. ictaluri has several other genes involved with virulence, first identified using Signature
Tagged Mutagenesis (63), but we will now focus on those involved with secretion systems.
12
Edwardsiella ictaluri Secretion Systems
A recent paper, in addition to the NCBI database, shows that E. ictaluri has 5 known
types of secretion systems: Type I, Type II, Type III, Type IV and Type VI (T1SS, T2SS, T3SS,
T4SS and T6SS), all of which are typically involved in virulence or aiding the bacterium in some
manner (64, 65). In E. ictaluri, several papers describe the role of virulence in the T3SS (58, 63,
66), important to this work, and also the T6SS (66, 67).
Our focus will be on the T3SS, but first a brief discussion of the T6SS. The T6SS
transfers substrates in a contact dependent manner. T6SS’s consist of two main proteins,
hemolysin coregulated protein (Hcp) and valine-glycine repeat protein (VgrG) (68). Together
they form part or all of the T6SS apparatus, and they resemble bacteriophage tail and spike
proteins (68). The Hcp hexamer is about 4 nm (internal diameter) and can accommodate a
globular protein about 50 kDa, but Vgr is too narrow to allow it to pass so, it is proposed that
VgrG breaks off after target cell puncture (68). T6SS’s are known to target other bacteria and/or
eukaryotic cells, and some are involved in functions such as conjugation, gene regulation, and
cellular adhesion (68). T6SS’s may not always be relevant to pathogenicity because the majority
of bacteria that have T6SS are not pathogens and are found in bacteria inhabiting marine
environments, soil, and are often symbionts or commensals (68).
Pathogenic implications for the T6SS in Edwardsiella spp., exist (69). A study disrupting
T6SS effector evpP in E. tarda showed an attenuated effect in blue gourami, and additional
evidence showed that the T6SS is repressed by Fur, a protein that modulates gene expression in
bacteria (68). The T6SS of E. ictaluri was identified as homologous to the one found in E. tarda
and is necessary for virulence. Additionally, another study suggested that the T6SS is in a single
13
transcript and is regulated by EsrC, a T3SS protein (66). Although the T6SS is involved in
virulence and is the subject of much current research, our work focuses on the T3SS.
Type III secretion systems and Edwardsiella ictaluri
T3SS’s are found in a wide array of gram-negative bacteria, including Yersinia,
Salmonella, Escherichia, Pseudomonas, and Edwardsiella, and act to target specific functions in
the host cell that allow persistence and replication of the bacterium within the cell (70). T3SS’s
are comprised of a group of proteins that come together to form a needle like apparatus known as
the injectosome, which is used to inject effector proteins into the host cell either from outside of
the cell or from a vacuole in the cell (Figure 1.1) (71). Early research on T3SS’s in Salmonella
showed that it has two types, SPI-1, which is used for bacterial uptake into the cell and invasion
in the gut, and SPI-2, which is required for intracellular replication (51). Researchers were able
to show that some of the effectors were specific to the SPI-2 T3SS, and concluded that SPI-2 is
required for proliferation in macrophages in vivo, but could also have other functions (72).
Salmonella has a variety of effectors; some have a translocation sequence in their amino termini,
some contain leucine-rich repeats (LRR), and others are translocon proteins involved in the
assembly of the needle-like apparatus of the T3SS (73-75). E. tarda also codes a T3SS similar to
the SPI-2 T3SS found in Salmonella, and was found to have proteins homologous to
Salmonella’s apparatus forming proteins, chaperone proteins, and effector proteins (76, 77).
E. ictaluri encodes a T3SS structurally homologous to SPI-2 and E. tarda T3SS’s, where
E. ictaluri and Salmonella proteins share 42% to 77% identity at the protein level and genes are
arranged in similar operons (63, 66). The E. ictaluri genome encodes T3SS effector proteins both
in and outside of the T3SS pathogenicity island, and like the Salmonella SPI-2 T3SS, transports
14
effectors from the ECV to the host cytoplasm (66). As is true for Salmonella, the E. ictaluri
T3SS is necessary for replication and virulence, but regardless of similarity to other systems,
Figure 1.1: T3SS of E. ictaluri Modified from Pallen et al. (71). T3SS’s are comprised of a
group of proteins that come together to form a needle-like apparatus, given the ‘Esa’ designation,
known as the injectosome, which spans the inner and outer membrane of the bacterial cell wall
as well as forming a pore through the host vacuole membrane. The injectosome is used to inject
effector proteins, with the ‘Ese’ designation, from a vacuole in the cell. Some of these effector
proteins are shuttled to the injectosome by chaperone proteins with ‘Esc’ designations, while
others may contain translocation sequences.
15
effectors can carry out an array of different functions that do not necessarily translate between
species, so determining the function of E. ictaluri’s secretion system and it’s effectors is
important (63).
A study determined that the E. ictaluri T3SS was necessary for virulence in the host
because three genes, EsaU, and the two plasmids encoding effectors of the T3SS, pEI1 and pEI2,
were all attenuated when mutated (63). Baumgartner et al. found that the drop in pH in the
vacuole, driven by ATPase response to infection by the macrophage, triggers transcription of the
T3SS and activates the urease enzyme, which then increase the pH, ultimately allowing E.
ictaluri replication (58). The E. ictaluri T3SS is regulated by a two-component system EsrA, a
sensor kinase, and EsrB. This response regulator is homologous to two proteins responsible for
T3SS regulation in E. tarda and Salmonella (66). In low pH, EsrB is phosphorylated and
upregulates expression of the translocon genes and the transcriptional regulatory gene, esrC (66).
EsrC is then involved in regulating the T3SS, ultimately leading to the expression of the
remaining apparatus genes and the formation of the injectosome complex (66).
E. ictaluri T3SS effectors are also similar to Salmonella, where some are shuttled to the
injectosome by chaperone proteins, others contain translocation sequences, and some contain
LRR sequences (66, 70, 78, 79). Work to characterize the function of these effectors is ongoing
and will be of benefit for downstream applications to protect fish from ESC. A mutation in esaU,
which is part of the T3SS apparatus, prevents effector translocation and is completely attenuated
in vivo but does not protect fish after subsequent exposure to wild-type (WT) (63). This would
suggest that, in addition to being critical for virulence, one, if not several, of these effectors plays
an important role in stimulating a protective immune response in the catfish.
16
Currently, E. ictaluri is known to have nine T3SS effector proteins (Table 1.2) (63, 80).
Two effectors, EseH and EseI, were found in Open-reading frames on the plasmids, pEI1 and
pEI2, respectively (63). EseH was found to be a LRR, and EseI was determined to be highly
homologous to Shigella protein OspB (63). The other 7 are found in the chromosome (80).
Table 1.2: T3SS effectors of E. ictaluri. Modified from Dubytska et al. (80).
Effector GenBank accession
no.
Size (aa) Known or Putative
activity/description (reference)
EseG ABC60070 301 Vacuolar localization (63)
EseI AGF34188 151 Shigella OspB family of T3SS
effectors (81)
EseN ACR69124 214 Major Vault Protein C;
ERK1/2C (82)
EseO ACR69900 667 Shigella enterotoxin 2 and
ankyrin repeat protein
EseH AAF85955 619 aLRR, 5 repeats, E3 ubiquitin
ligase (81)
EseJ
ACR69526
599 LRR, 12 repeats, E3 ubiquitin
ligase
EseK Genomeb 930 LRR, 18 repeats, E3 ubiquitin
ligase; interacts with CD74
EseL
ACR68523 705 LRR, 6 repeats, E3 ubiquitin
ligase
EseM ACR68525 793 LRR, 11 repeats, E3 ubiquitin
ligase aLRR, leucine-rich repeat protein. bEseK was identified during E. ictaluri genome sequencing but was not found in the final
genome assembly. Analysis of genomic DNA using specific PCR primers confirmed its
presence in the genome.
Four of the effectors EseG, EseI, EseN, and EseO are unlike the other five, in that they
are not LRR’s. Currently EseN is the only effector with a described function. Recent work found
that EseN interacts with Major Vault Protein (MVP) as well as ERK1/2 (82). EseG, EseI, and
EseO currently have unknown functions, but we can speculate what their roles are based on their
appearance and known role in other species. EseG shares a high degree of homology with its
namesake in E. tarda, which functions to destabilize microtubules (83). EseI shares similarity
17
with Shigella flexneri OspB, which reduces inflammatory cytokine production in host cells (51),
and EseO is an ankyrin repeat protein that shares homology with ShET2 in Shigella and E. coli,
which is responsible for upregulating IL-8 in epithelial cells in Shigella infections (80).
BLAST analysis of the LRR effectors showed that all five have a translocation domain
in the amino terminus, an E3 ubiquitin ligase domain in their carboxy terminus, and 5 to 18
leucine-rich repeats in the core of the protein (80). Each of these effectors were shown to share
homology with similar proteins in other species. For example, EseK shares 58% identity with
SspH2 from S. enterica, and 42% identity with SlrP of S. typhimurium. Leucine rich repeats
drive the overall size and shape of the solenoid structure of each effector and determine the
nature of the target protein for each effector. As a result, the effectors bind entirely different
proteins and carry out vastly different functions despite a high degree of amino acid homology
(84). Additionally the translocation domain was shown to be functional, meaning each LRR
effector can translocate out of the ECV without the need of a chaperone (80). The ubiquitin
ligase domain likely plays a role in determining the fate of the host proteins bound by the
effector (80).
Additionally, research showed that all effector deletions tested had an attenuated effect
on replication in CCO’s, and three effectors, EseJ, EseK, and EseN also had attenuated
replication, albeit not as severely, in HKDM compared to WT (80). EseK was secreted by the
T3SS and was translocated in HKDM, but not in channel catfish ovary cells (CCOs) (80). This
could suggest that EseK plays a specific role in antigen-presenting cells (APCs) or phagocytes.
Also, unpublished work from other members of the Thune lab using a yeast two-hybrid assay on
all effectors found that EseK likely interacts with CD74 of the host cell.
18
Limited research on the LRR’s means their effects on pathogenesis are largely unknown.
Because of the potential ramification of EseK’s interaction with CD74, and the limited
information suggesting that EseK plays an important role in virulence of E. ictaluri, one focus of
this work is to determine the effect of EseK on cell mediated immunity.
Objectives and Hypotheses
The hypothesis driving this work is that E. ictaluri is capable of persisting in and
replicating in the channel catfish because it can evade cell-mediated immune (CMI) responses of
the host. Secondly, we hypothesis that EseK aids WT E. ictaluri in the evasion of CMI
responses. Therefore, the objective of this research is to better characterize an E. ictaluri
infection, focusing on the potential for cellular responses and, additionally, to characterize the
T3SS effector, EseK, relative to WT. In order to do this, work focused on uncovering more
information related to E. ictaluri’s role in cellular responses both in the HKDM and in vivo, and
to characterize the role of EseK in this response.
The second chapter of this dissertation characterizes EseK, both confirming its host
protein binding partner and the potential use of an EseK mutant to establish protection of catfish
against WT exposure. Previous work in the lab showed that EseK was translocated in a pH-
dependent manner (80) and suggested, using a yeast-2-hybrid assay, that the binding partner of
EseK is CD74 (unpublished). A co-immunoprecipitation assay was carried out to verify EseK
and CD74 interaction. Because CD74 is highly involved in adaptive immune responses, an eseK
mutant strain was compared to WT to determine relative virulence, and vaccination assays were
carried out with ΔeseK to determine if a lack of EseK could provide protection against WT
exposure, possibly indicating a role for this protein in reducing cell-mediated immunity (CMI).
19
The third chapter of this dissertation aims to determine the modulation of HKDM in the
presence of WT, and ΔeseK strains with special attention given to pathways involved in
immunity and cell death. The fourth chapter of this dissertation aims to characterize the immune
modulation of fish infected with WT relative to a control, and to what end EseK may be involved
in that response. The experiments in this chapter focused primarily on genes related to T cells
and cellular responses in HK and peripheral blood leukocyte (PBL) samples and supporting data
of leukocyte cell dispersion was collected using flow cytometry.
Finally, the fifth chapter provides overall conclusions for this work, tying the previous
chapters together. Briefly, we found that E. ictaluri is downregulating the CD40-CD40L
pathway, ultimately allowing it to evade most T cell responses, and additionally, pushes HKDM
towards autophagy instead of apoptosis, allowing it to persist in the cell. We also found that
EseK interacts with CD74 in channel catfish HKDM, which is a highly pleiotropic protein
involved in many immune related responses. The ΔeseK strain does provide some protection
against WT exposure, giving credence to important functions for the EseK-CD74 interaction, but
under the tested parameters, EseK, was not implicated in evasive immune responses at the
transcriptional level.
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Microbiol 53:573-586.
77. Zheng J, Li N, Tan YP, Sivaraman J, Mok Y-K, Mo ZL, Leung KY. 2007. EscC is a
chaperone for the Edwardsiella tarda type III secretion system putative translocon
components EseB and EseD. Microbiology 153:1953-1962.
78. Bhavsar AP, Brown NF, Stoepel J, Wiermer M, Martin DD, Hsu KJ, Imami K, Ross CJ,
Hayden MR, Foster LJ, Li X, Hieter P, Finlay BB. 2013. The Salmonella type III effector
SspH2 specifically exploits the NLR co-chaperone activity of SGT1 to subvert immunity.
PLoS Path 9:e1003518.
79. McShan AC, De Guzman RN. 2015. The bacterial type III secretion system as a target for
developing new antibiotics. Chem Biol Drug Des 85:30-42.
80. Dubytska LP, Rogge ML, Thune RL. 2016. Identification and characterization of putative
translocated effector proteins of the Edwardsiella ictaluri type III secretion system.
mSphere 1:e00039-16.
27
81. Fernandez DH, Pittman-Cooley L, Thune RL. 2001. Sequencing and analysis of the
Edwardsiella ictaluri plasmids. Plasmid 45:52-6.
82. Dubytska LP, Thune RL. 2018. Edwardsiella ictaluri type III secretion system (T3SS)
effector EseN is a phosphothreonine lyase that inactivates ERK1/2. Dis Aquat Org
130:117-129.
83. Xie HX, Yu HB, Zheng J, Nie P, Foster LJ, Mok Y-K, Finlay BB, Leung KY. 2010.
EseG, an effector of the type III secretion system of Edwardsiella tarda, triggers
microtubule destabilization. Infect Immun 78:5011-5021.
84. Dubytska LP, Rogge ML, Thune RL. 2016. Identification and Characterization of
Putative Translocated Effector Proteins of the Edwardsiella ictaluri Type III Secretion
System. mSphere 1.
28
CHAPTER 2. ESEK HOST INTERACTION AND PROTECTIVE ABILITY
AGAINST SUBSEQUENT WILD-TYPE EXPOSURE
Introduction
Edwardsiella ictaluri is a gram-negative bacterium of the phylum proteobacteria and
family Enterobacteriaceae, which includes other pathogens such as Salmonella, Escherichia, and
Yersinia spp. The bacterium Edwardsiella ictaluri causes the disease Enteric Septicemia of
Catfish (ESC), which causes 20-30% loss to catfish production amounting to millions of dollars
in loss annually (1). This is pertinent because the United States catfish industry has consistently
accounted for one-third to almost one-half of U.S. generated aquaculture revenue annually (2).
Reports indicate that production of all U.S. aquaculture, including catfish production, will need
to increase in the coming years to meet market demand, and improving the efficiency of
production will be essential to this process (3, 4). One avenue that will aid in catfish production
will be the reduction of loss to disease. Several common strategies currently in use to reduce
disease losses are antibiotic treatment, food restriction, and hybrid catfish production (1, 5).
Another avenue that will aid the reduction in loss of catfish will be a better understanding of the
bacterium, specifically concerning modifications of the host function and physiology.
Knowledge of the effects of protein modifications by the bacterium on host metabolism will aid
in designing smarter vaccine candidates in the future, whether that be a single attenuated mutant
or coupled mutations. One strategy is using a live attenuated vaccine to promote natural
immunity to E. ictaluri. Aquavac-ESC, a previously developed live vaccine, showed limited
efficacy, but significant research is ongoing to develop an efficacious product (6-8).
One potential knock-out target for such a vaccine is the Type III Secretion System
(T3SS), which is required for virulence and intracellular replication (9). Gram-negative bacteria,
29
including Salmonella, Escherichia, Yersinia, and Edwardsiella have T3SS’s that can target
specific functions in the host cell to allow persistence and replication of the bacterium within the
cell (9, 10). T3SS’s are composed of a group of proteins that come together to form a needle-like
apparatus known as the injectosome, which is used to inject effector proteins into the host cell
cytosol, either from outside of the cell or from a vacuole within the cell (11). The latter is the
case of E. ictaluri, which utilizes the T3SS to translocate effectors from the Edwardsiella-
containing vacuole (ECV) to the host cytoplasm (12).
Some of these effector proteins are shuttled to the injectosome by chaperone proteins,
which can be specific to particular effectors, while others may contain a translocation sequence
(10, 13-15). The T3SS of E. ictaluri has nine known effectors, five of which contain leucine-rich
repeats (LRR’s), causing them to share a high degree of homology both with each other and with
effectors of other species such as Salmonella (12). Although high degrees of homology exist
among effectors from different organisms, each effector is still unique to a particular pathogen
and they often carry out different functions in the host despite their homology (12).
For instance, the effector protein EseK was identified on the chromosome of E. ictaluri
and was determined to contain 18 leucine-rich repeats (LRR), a ubiquitin ligase domain in the
carboxyl terminus, and a functional translocation sequence at the amino terminus (12). Phyre 2
modeling showed 77% of the residues at greater than 90% confidence and indicated that EseK
shares a 58% identity with SspH2 from S. enterica, and a 42% identity to the S. typhimurium
effector SlrP (Figure 2.1) (16). While EseK shares homology with SspH2 and SlrP, the function
of EseK can differ from SspH2 and SlrP because both the bacterium as well as the number of
LRRs affects the target protein for EseK by changing the overall binding shape of the protein
30
(12, 17). A translocation assay showed that EseK was translocated under neutral pH to the host
cell cytoplasm in HKDM (18).
Figure 2.1: Phyre 2 Model of EseK. Protein residues are colored in rainbow format with red on
the N terminus and blue on the C terminus Phyre 2 modeling was able to model 77% of the
31
residues at greater than 90%confidence and suggests that EseK shares a 58% identity with SspH2
from S. enterica, and a 42% identity to the S. typhimurium effector SlrP.
Additionally, previous yeast two-hybrid experiments in the lab suggest a protein-protein
interaction with CD74, which could mean that EseK plays a specific role in antigen presentation
in dendritic cells and macrophages (data unpublished). The overarching hypothesis of this work
is that WT E. ictaluri can evade cell-mediated immune responses, and this preliminary evidence
led to the specific hypothesis that EseK could aid E. ictaluri in evasion of the host immune
response. In this chapter we began to address the potential for EseK to be involved in virulence
by confirming its host binding partner and potential protection of catfish against WT exposure.
Initially an EseK::3XFLAG fusion was constructed that could be specifically detected with
3XFLAG antibody in the presence of the four other LRR effectors, and used to confirm that
CD74 is the specific binding partner of EseK. Given the role of CD74 in host cell immunity, we
carried out several vaccination experiments, believing an eseK mutant strain (ΔeseK) could be
protective against ESC. We observed that ΔeseK has an attenuated effect on pathogenesis at
target doses while providing protection from subsequent exposure to WT.
Materials and Methods
Bacterial Growth. Strains and plasmids used in this work are listed in Table 2.1.
Edwardsiella ictaluri strains were grown overnight (O/N) at 28C with aeration from frozen
cultures stored at -80C in 5mL aliquots of BHI-porcine with 15% glycerol (Sigma-Aldrich, St.
Louis, MO). Escherichia coli strains were grown in Luria-Bertani (LB) broth at 37C with
aeration and antibiotics added where appropriate. Antibiotics used were 200 ug/mL Antibiotics
used were 200 µg/mL Ampicillin (Amp) and 20 µg/mL Colistin (Col). These starter cultures
were then used for downstream assays.
32
Table 2.1: Strains and plasmids utilized in the scope of this research project.
Strain or
Plasmid
Description Source
Edwardsiella
ictaluri 93-146
Wild-type E. ictaluri isolated in 1993
from moribund channel catfish in a
natural outbreak of ESC on a
commercial farm
LSU aquatic animal diagnostic
laboratory
eseK::3XFLAG eseK::3XFLAG in ΔeseK E. ictaluri This study
ΔeseK E. ictaluri 93-146 Δ(eseK1-2202) This Study
65ST 93-146 esaU::Tn5Km2 (9)
pRE107 R6K ori mob sacB1; Apr; suicide vector
used for allelic exchange
(19)
CC118 λpir Δ (ara-leu) araD Δ lacX74 galE galK
phoA20 thi-1 rpsE rpoB argE(Am)
recA1 λpir lysogen
(20)
S17-1 λpir Tp Sm thi pro recA HsdR-HsdM+; RP4-
2-Tc::Mu::Km Tn7 λpir
(21)
pBBR1-MCS4 Broad host range expression vector; Apr (22)
Strain Generation. An eseK mutant strain (ΔeseK) was generated from wild-type E.
ictaluri 93-146 (WT) (Appendix 2). Overlap-deletion PCR using the primer sets P190, P191,
P192, and P197 allowed for the amplification of a 5’ portion of eseK and a 3’ portion of eseK
(Table 2.2 and Appendix 2, Supplemental Figures 2.1, 2.2,and 2.3). These two fragments
contained overlapping sequences of the other fragment as linkers that were mixed and amplified
using primers P190 and P192 to delete 2200 bp of eseK beginning at the ATG start site at the N-
terminus. This truncated eseK product was then ligated to pRE107, a suicide vector, and
transformed into E. coli CC118 λpir for sequence verification before transformation into E. coli
S17-1 λpir. E. coli S17-1 λpir containing the construct was then conjugated to WT on BA plates
O/N at 28C. Selection occurred by a double crossover generating the ΔeseK strain.
33
Briefly, the plasmid and WT were selected on BHIColAmp at 28C. Colonies were then
patched to BHICol at 28C. Finally, patched colonies were struck onto BHIcolsucrose at 28C to
allow for selection of a second crossover of ΔeseK into the WT chromosome and deletion of the
pRE107 plasmid. Verification of the construct was done by PCR and DNA sequencing. The
eseK::3XFLAG fusion strain was generated using a forward primer upstream of the native
promoter (Table 2.2) and a downstream promoter, which was designed to include a 3X FLAG
sequence in frame with the eseK sequence and followed by a stop codon. This amplicon was
added to the pBBR1-MCS4 plasmid and inserted into the ΔeseK E. ictaluri strain to create a
complemented strain (Appendix 2, Supplemental Figure 2.4).
Table 2.2: Primer sets.
Primer name/
description
Sequence Source
P119. eseK
Forward SacI RE
gccgatgagctcGTGATCTACACAACGAATGCTATCGAGT Thune
Lab
OL1.
eseK::3XFLAG
Reverse XbaI RE
gaagattctagaCTActtgtcatcgtcatccttgtagtcgatgtcatgatctttataatca
ccgtcatggtctttgtagtcTACAGGGGACGCATCTAGCAA
This
Study
P190. muteseK
Forward 5’ SacI RE
GGACTATCTGAGCTCTCTGGCTCAATGTGCTGACAG
AGCTGAAG
This
Study
P191. muteseK
Forward 3’
CCAATGAATCAATAGGAAAATTGTACTAACGATATC
CCGGGGCTCGTGTCGGTAG
This
Study
P192. muteseK
Reverse 3’ XbaI RE
CACGATGCCTCTAGATCAGTTTATGCCAGGGAATGC
TATACAGGGGACGCATC
This
Study
P197. GC-muteseK
Reverse 5’
CTACCGACACGAGCCCCGGGATATCGTTAGTACAAT
TTTCCTATTGATTCATTGG
This
Study
Secretion Assays. E. ictaluri cultures were grown according to Dubytska et al. under low
phosphate conditions in a defined minimal media (MMP) specific for E. ictaluri growth (18, 23).
34
Briefly, E. ictaluri starter cultures were pelleted at 3,000 rpm (accuSpin™ 3R, Fisher Scientific)
washed once in MMP, and resuspended in MMP at 1 part starter culture to 5 parts MMP at 28C
with aeration for 4 hours. The pH of this culture was then neutralized to pH 7 to promote effector
secretion (18). After 90 minutes, cultures were pelleted, and the supernatant containing the
secreted proteins were collected. This was then used for immunoblot and Co-IP assays.
HKDM Collection. HKDMs were collected and used for downstream assays according
to Booth et al (24). Briefly, fish were euthanized in 1g/L Tricaine-S (Pentair). Head kidneys were
removed, homogenized through a sterile double stainless-steel mesh tissue sieve (280 and 140
µm) (Sigma Chemical co.), and suspended at approximately 1 X 107 cells/mL in channel catfish
macrophage medium (CCMM) (25). Five ml per well was added to 6 well plates (Sigma-
Aldrich). Cells were allowed to adhere overnight at 28C in a 5% CO2 atmosphere, washed three
times in RPMI, resuspended in CCMM and counted.
Co-IP. Co-IP experiments, performed on three separate occasions, were carried out using
the Dynabeads® Co-Immunoprecipitation Kit (Thermo Fisher Scientific) in conjugation with pre-
coated anti-FLAG® M2 magnetic beads (Sigma-Aldrich). Briefly, HKDM were lysed using lysis
buffer B, provided by the kit. Lysates were then allowed to incubate with fresh anti-FLAG
coated magnetic beads, to allow for pre-adsorption of non-specific protein binding. Pre-adsorbed
lysates were then allowed to incubate with fresh anti-FLAG coated magnetic beads, and
supernatant produced from eseK::3XFLAG that was concentrated approximately 1:100 using an
Amicon® Ultra-15 10K centrifugal filter device (EMD Millipore Corp). After incubation, the
beads were washed, and the co-immunoprecipitated proteins were eluted from the beads with a
proprietary kit-eluate containing lithium dodecyl sulfite (LDS). Eluate was run on LDS-PAGE,
and proteins of interest were verified by mass spectrometry.
35
Polyacrylamide Gel Electrophoresis. Analysis with sodium dodecyl sulfate (SDS) or
LDS-PAGE was performed using 4-20% gradient polyacrylamide gels (Bio-Rad) following the
manufacture’s protocol. Following separation, proteins were either stained or transferred to a
PVDF membrane. Direct staining was carried out using Blue BANDit™ (VWR Life Science),
SYPRO® Ruby Red (Invitrogen), or Silver Reagent Concentrate (Bio-Rad). Gel transfer for
Western blotting was carried out using the iBlot™ (Invitrogen) according to manufacturer
protocols.
Mass spectrometry was completed in the LSU Mass Spectrometry Core Facility in the
Department of Chemistry. Briefly, protein samples cut from a polyacrylamide gel underwent
tryptic digest. Tryptic peptide peaks were identified by MALDI-TOF MS analysis. Observed
peaks were compared with theoretical mass values from in-silico digestion using the Peptide
Mass program (http://web.expasy.org/peptide_mass/).
Western Blot Analysis. Briefly, membranes were allowed to block in 5% BSA or 5%
milk for one hour at room temperature (RT) or overnight (O/N) at 4C. The anti-FLAG primary
antibody, THETM DYKDDDDK Tag, Mouse mAb (Genscript Biotech) was added at 1 ug/mL for
one hour at RT. Following this, mouse secondary antibody, IRDye 680RD donkey anti-Mouse
IgG (H+L) (LI-COR Biosciences) was used for detection on an Odyssey® CLx imager (LI-COR
Biosciences).
SimpleWES Electrophoresis and Detection. The WES system (Protein Simple) was
used for putative target protein detection. Briefly, 5 uL of equal concentrations of each sample
were loaded into wells and separated by capillary force with the 12-230 kDa Separation Module
(Protein Simple). Detection occurred using Anti-FLAG primary with the Anti-Mouse Detection
Module (Protein Simple). Detection followed standard WES cycling parameters.
36
Fish Care. Channel catfish egg masses were received from a Morehead, Mississippi
catfish farm with no history of ESC outbreaks. The eggs were then disinfected with 100 ppm free
iodine and hatched in a closed recirculating system in the specific-pathogen-free (SPF)
laboratory at the LSU School of Veterinary Medicine. Fish were reared in systems containing
four 350 L fiberglass tanks connected to a 45 L recirculating-bead filter (Aquaculture Systems
Technologies). Water quality was tested at least three times a week, and the temperature was
constantly monitored to ensure optimal conditions for fish wellness. Specific pathogen-free
channel catfish fingerlings ranging from 12.5, 20, and 32.5 g in separate experiments were
moved at 25 fish each per 20 L flow-through tank. Catfish were fed 2% to 3% body weight every
other day and allowed to acclimate 28 days before vaccination (26). Pre-vaccination, catfish
were re-sorted to assure 25 fish per tank. All experiments were carried out following protocols
approved by the Institutional Animal Care and Use Committee and the Inter-Institutional
Biological and Recombinant DNA Safety Committee of Louisiana State University.
Immersion Assays. Starter cultures of the WT strain E. ictaluri 93-146 and the ΔeseK
strain were used to inoculate up to 400 mL BHI per 2 L flask at 28C and cultures were allowed
to incubate until each bacterial treatment reached an OD600, reflecting a concentration of 1 X 1010
colony-forming unit’s (CFU) per mL. The culture was then diluted as required per dose-
treatment for the inoculation of the catfish. The bacterial concentration was subsequently verified
by drop plating ten-fold serial dilutions in triplicate on trypticase soy agar supplemented with 5%
defibrinated sheep blood (BA) (27).
Vaccination. During vaccination, each tank was lowered to 4 L or 8 L of water using a
standardized adapter. Cultures of ΔeseK grown in BHI-porcine was then added to 4 tanks each
for the preliminary experiment, and six tanks each for Trials 1 and 2 assigned randomly. This
37
allowed for the following doses: preliminary experiment, ΔeseK 1.8 X 108 cfu/mL, and WT 1.7
X 108; for Trial 1, E. ictaluri ΔeseK 1.1 X 107 cfu/mL; for Trial 2, ΔeseK 5.1 X 106 cfu/mL. An
uninfected BHI-Sham served as a negative control. After one hour the tanks were allowed to
return to 20 L. Catfish were monitored daily for mortalities, which typically occurred within 14
days (26). E. ictaluri presence was confirmed in mortalities by inoculating liver samples onto BA
plates.
Challenge. At 4 and 8 weeks following vaccination, 3 tanks per vaccination treatment
were challenged using WT at the following doses: preliminary 3 X108 cfu/mL, Trial 1 challenge
4 week: 1.5 X108 cfu/mL and challenge 8 week: 1.6 X108 cfu/mL, Trial 2 challenge 4 week:
eseK: 1 X108 cfu/mL, challenge 8 week: 1.2 X108 cfu/mL following the same bacterial
immersion protocol described for the vaccination. Catfish were monitored for 14 days, and E.
ictaluri presence was confirmed in mortalities by streaking liver samples onto BA plates.
Statistics. Significance among treatments was determined by taking the average cumulative
percent survival of each treatment and carrying out a one-way ANOVA with Tukey’s posthoc
test and confidence interval of 95% using PRISM, Graphpad version 5.00.288.
Results
EseK::3XFLAG Functionality. The EseK::3XFLAG strain was determined to have
three ]plasmids, the two native plasmids pEI1 and pEI2, which are 4807 bp and 5643 bp
respectively, and a third plasmid approximately 8261 bp in size which correlates to the size
expected for the pBBR1-MCS4 plasmid carrying the EseK::3XFLAG fusion (Figure 2.2A) (28).
Catfish infected with eseK::3XFLAG at 1 X108 cfu/mL and WT at 1 X108 cfu/mL showed no
significant difference in mortality, with 26.6 and 21.3 percent survival observed, respectively
(Figure 2.2B). Functional secretion of EseK::3XFLAG, 105 kDa, was determined by
38
immunoblot using the eseK::3XFLAG strain and WT strain grown at conditions favorable for
EseK translocation, detected using the anti-FLAG monoclonal antibody, and also using the WES
detection system (Figure 2.2C,D). No detection occurred in the WT strain, while detection was
visible in the EseK::3XFLAG strain. This band was verified as EseK with a FLAG fusion by
mass spectrometry (data not shown).
Figure 2.2: EseK::3XFLAG Confirmation. A) MW marker (1) followed by plasmid preps of
supercoiled DNA from ΔeseK (2), WT (3), and eseK::3XFLAG (4). eseK::3XFLAG regulates 3
plasmids, the native pEI1, 4807 bp, and pEI2, 5643 bp, in addition to pBBR1-
MCS4+EseK::3XFLAG, 8261 bp. B) Survival of catfish infected with WT or EseK::3XFLAG
strains each at 1 X108 cfu/mL. No significant difference in survival is detected. C) Western blot
detection of MW marker (1), eseK::3XFLAG using anti-FLAG in the supernatant of
EseK::3XFLAG at pH 5 (2), EseK::3XFLAG at pH 7 (3), WT at pH 5 (4), WT at pH 7 (5);
compared to standard protein marker (1). D) WES detection of EseK::3XFLAG in
39
eseK::3XFLAG pH7 (102 kDa) and WT pH7 supernatants with an ERK1/2 (47 kDa) control
used for WES assay performance control.
EseK and CD74 Interaction. Co-IP using FLAG antibody-coated magnetic beads
confirmed CD74 and EseK interaction. Staining detected two distinct bands in a polyacrylamide-
gel of the co-immunoprecipitated sample (Figure 2.3). Mass spectrometry analysis confirmed
the two proteins as EseK and CD74 (Figure 2.4).
Figure 2.3: SYPRO Ruby Red Stain of Co-IP: of protein ladder (1), concentrated
EseK::3XFLAG supernatant (2), and co-immunoprecipitated proteins (3). EseK::3XFLAG is
predicted to be 105 kDa, and CD74 is predicted to be 26 kDa.
40
Figure 2.4: Positional hits from mass spectrometry tryptic digest of proteins excised from bands
after Co-IP. The top amino acid sequence is EseK showing the positional hits indicated by Mass
spectrometry, including the 3XFLAG region. The bottom amino acid sequence is channel catfish
CD74, showing the positional hits indicated by Mass spectrometry.
Preliminary Vaccination. A preliminary vaccination experiment determined virulence
of ΔeseK at varying doses. While ΔeseK and WT at the highest dose showed no significant
difference, with a mean of 28 and 8% respectively, ΔeseK had fewer mortalities, a correlation
also seen in prior preliminary lab experiments (data not shown). The remaining doses proved to
be significantly attenuated, where survival improved, showing 95% survival in ΔeseK 1.8 X107
41
cfu/mL, 99% survival in ΔeseK 1.8 X104 cfu/mL, and 100% survival in all other doses (Figure
2.5A).
Figure 2.5: Preliminary Vaccination and Challenge A) Fish were infected with E. ictaluri wild
type 1.8 X108 cfu/mL, ΔeseK 1.8 X108 cfu/mL, ΔeseK 1.8X107 cfu/mL, ΔeseK 1.8 X106 cfu/mL,
ΔeseK 1.8 X105 cfu/mL, ΔeseK 1.8 X104 cfu/mL, Sham-BHI, or Control. Deaths were monitored
for 14 days post vaccination. B) All channel Catfish were challenged with wild type 2.9 X108
cfu/mL. Deaths were monitored for 14 days PV.
Preliminary Challenge. Seven weeks post-vaccination (PV), catfish were exposed to
WT at a dose of 2.9 X108 cfu/mL. Fish vaccinated with doses as low as 1.8 X105 cfu/mL had
84.5% survival, similar to 71.7% observed in 65ST. Doses as low as ΔeseK 1.8 X105 cfu/mL
42
provided protection, as 83.5% of catfish survived, and 99 to 100% survived in the ΔeseK 1.8
X106 cfu/mL and ΔeseK 1.8 X107 cfu/mL treatments (Figure 2.5B). Interestingly, 54.3% of
catfish survived the ΔeseK 1.8 X104 cfu/mL dose, so remaining experiments incorporated this
dosage range.
Safety of ΔeseK. Two separate experiments were then performed on catfish fingerlings
using the optimal dosage for protection from the preliminary data of 1.1 X107 cfu/mL to 5.1
X104 cfu/mL.
In both experiments, 6 tanks each containing 25 fish were vaccinated with ΔeseK at doses
from 1.1 X105 cfu/mL to 1.1 X107 cfu/mL for the first experiment (Table 2.3), and 5.1 X104
cfu/mL to 5.1 X106 cfu/mL for the second experiment (Table 2.3). This range appeared safe,
where mortalities were only seen in the highest doses of 5.1 X106 cfu/mL to 1.1 X107 cfu/mL
between the two experiments, 4.7%, and 0.7% respectively.
Table 2.3: Safety of ΔeseK vaccinated fish. Percent survival observed per treatment per tank
from Vaccinations during Trial 1 and Trial 2 followed by average (Avg) percent survival
observed per treatment.
Trial 1 Vaccination Survival Per Tank Avg
ΔeseK 1.1 X107
cfu/mL 100 100 100 96 100 100 99.3
ΔeseK 1.1 X106
cfu/mL 100 100 100 100 100 100 100.0
ΔeseK 1.1 X105
cfu/mL 100 100 100 100 100 100 100.0
Sham-BHI 100 100 100 100 100 100 100.0
Trial 2 Vaccination Survival Per Tank Avg
ΔeseK 5.1 X106
cfu/mL 100 92 80 100 100 100 95.3
ΔeseK 5.1 X105
cfu/mL 100 100 100 100 100 100 100.0
ΔeseK 5.1 X104
cfu/mL 100 100 100 100 100 100 100.0
Sham-BHI 100 100 100 100 100 100 100.0
43
Early WT Challenge. Challenges were carried out on three of the six tanks per dose 4
weeks PV to determine if catfish can mount a relatively quick response to subsequent WT
challenge. In the first experiment, fish received WT at 1.5 X108 cfu/mL, and in the second trial,
fish received WT at 1 X108 cfu/mL. In the first experiment (figure 2.6A), the ΔeseK 1.1 X107
cfu/mL vaccine dose had 100% survival, the ΔeseK 1.1 X106 cfu/mL dose had 92% survival, and
the ΔeseK 1.1 X105 cfu/mL dose had 74.3% survival. The second trial (figure 2.6B) followed a
similar trend where 100% survival was observed in ΔeseK 5.1 X106 cfu/mL, 97.3% survival was
observed in ΔeseK 5.1 X105 cfu/mL, and 78.7% survival was observed in ΔeseK 5.1 X104
cfu/mL. This compared to the Sham-Challenged, which only had 17.3% and 4% survival for the
first and second trials. This suggests that doses of 1.1 X107 cfu/mL to 5 X105 cfu/mL produce
high levels of protection against subsequent exposure to WT, while survival begins to decline
between the 5.1 X105 cfu/mL and 1.1 X105 cfu/mL dose to 74.6%, where the lower doses of 1.1
X105 cfu/mL to 5.1 X104 cfu/mL begin to decline in protection.
Late WT Challenge. Assessment of late survival occurred at 8 weeks post-vaccination,
where the final 3 of 6 tanks of catfish received the WT dose at 1.6 X108 cfu/mL for Trial 1
(Figure 2.7A) and 1.2 X108 cfu/mL for Trial 2 (Figure 2.7B). In the first experiment it was
determined that 97.3% of the ΔeseK 1.8 X107 cfu/mL fish survived, 100% of the ΔeseK 1.1 X106
cfu/mL treatment survived, and 94.6% of the ΔeseK 1.1 X105 cfu/mL fish survived (figure 2.7B).
During the second Trial 100% of the ΔeseK 5.1 X106 cfu/mL fish survived, but reduced
survivability of 74.7% and 28% resulted in the ΔeseK 5.1 X105 cfu/mL, and the ΔeseK 5.1 X104
cfu/mL respectively (Figure 2.7B). Together the trend suggests that the highest doses of ΔeseK
1.1 X107 cfu/mL to 1.1 X105 cfu/mL are protective, but this decreases at the 1.1 X105 doses
through the 5.1 X104 doses.
44
Figure 2.6: Early Exposure to WT. A) Trial 1. Mean cumulative percent survival with standard
error of the mean of 3 tanks per dose of ΔeseK 1.1 X107 cfu/mL, ΔeseK 1.1 X106 cfu/mL, ΔeseK
1.1 X105 cfu/mL challenged with WT 1.5 X108 cfu/mL. B) Trial 2. Mean cumulative percent
survival with standard error of the mean of 3 tanks per dose of ΔeseK 5.1 X106 cfu/mL, ΔeseK
5.1 X105 cfu/mL, ΔeseK 5.1 X104 cfu/mL challenged with WT 1 X108 cfu/mL. Significant
differences in groups represented by letters.
45
Figure 2.7: Late WT challenge. A) Trial 1. Mean cumulative percent survival with standard error
of the mean of 3 tanks per dose of ΔeseK 1.1 X107 cfu/mL, ΔeseK 1.1 X106 cfu/mL, ΔeseK 1.1
X105 cfu/mL challenged with WT 1.6 X108 cfu/mL. B) Trial 2. Mean cumulative percent
survival with standard error of the mean of 3 tanks per dose of ΔeseK 5.1 X106 cfu/mL, ΔeseK
5.1 X105 cfu/mL, ΔeseK 5.1 X104 cfu/mL challenged with WT 1.2 X108 cfu/mL. Significant
differences in groups represented by letters.
Discussion
The high degree of homology among the E. ictaluri T3SS LRR effectors makes them
impossible to detect from one another with specific antibody. The 3XFLAG tag was chosen
46
because tagging can alter protein function and expression, and the 3XFLAG tag strategy proved
effective on T3SS effectors SopB and SspH1 in Salmonella (13, 29). Using an eseK::3XFLAG
fusion created under the control of EseK’s native promoter on pBBR1-MCS4 and inserted into
the ΔeseK strain, effectively resulted in a complemented strain. The plasmids of eseK::3XFLAG
exhibited regulation at the same relative abundance of the two native plasmids in the WT and
ΔeseK strain. The virulence of eseK::3XFLAG was the same as the WT, and the protein was
able to be secreted and detected specifically in the supernatant. This allowed completion of a Co-
IP assay while minimizing specificity issues associated with false negatives (30). A previous
experiment in the lab utilizing a yeast-2-hybrid assay gave the first indication that EseK interacts
with CD74. The Co-IP assay using bacterial supernatant and a HKDM lysate confirmed the
interaction between EseK and CD74. Carrying out this experiment with HKDM leaves other
potential target proteins unidentified, but reduced the potential for non-specific protein binding
from an increased protein pool (30). Mass spectrometry then identified the proteins as CD74 and
EseK. This is of interest because CD74 carries out a wide array of roles in the host immune
response (31), including chaperoning MHC class II during its assembly and migration from the
ER to the cell surface (32).
CD74 also acts as a ligand-receptor for macrophage migration inhibitory factor (MIF)
regulation and exhibits a role in cross-presentation to MHC class I (31). It is possible that the
interaction of EseK with CD74 means that it is involved with suppression of cell-mediated
immune responses, and that its deletion may improve protection. Based on this hypothesis, the
virulence of ΔeseK was determined relative to the WT, T3SS null mutant (65ST) and Sham-BHI.
Early exposure to ΔeseK at 4 weeks PV found that protection is very high for all doses. A later
exposure at 8 weeks PV saw a decline in protection from WT. The reduced efficacy at eight
47
weeks could result because the dosage given 8 weeks prior to challenge was too low to mount an
adequate antibody response after 8 weeks. A 1993 study found that fish re-exposed to WT after
a natural ESC outbreak showed a correlation of antibody titer to susceptibility to disease after re-
infection, and that some fish produce low or no antibody titer after initial exposure (33). It was
also speculated that re-stimulation with antigen could improve antibody titers. Literature
suggests that antibody accumulation is less important than cell-mediated responses in preventing
ESC because E. ictaluri is an intracellular pathogen that survives and replicates within host cells,
where it is protected from antibody (34, 35). Moreover, previous reports of fish surviving
outbreaks of ESC following immersion challenge were determined not to be antibody-related
(36), giving further credence to a major role for CMI (35). This could suggest that ΔeseK is
producing CMI responses at higher doses, but not robustly enough at lower doses to be
protective at 8 weeks post- vaccination. These data support the overarching hypothesis that WT
is capable of preventing CMI to persist in the host, because this is likely the arm of immunity
most capable of targeting an intracellular pathogen. Additionally, this immunity is of interest in
the case of EseK because an interaction with CD74 could have implications on limiting antigen
presentation and preventing a strong T cell response.
Our current findings determined that EseK interacts with catfish CD74 in HKDM, and that
protection could be observed in response to exposure to the ΔeseK strain. Future work will aid
our understanding of EseK’s role in the cell-mediated immune response.
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safe and efficacious as a live, attenuated vaccine. J Aquat Anim Health 11:358-372.
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51
CHAPTER 3. NAÏVE HEAD KIDNEY DERIVED MACROPHAGES
FAVOR M1 POLARIZATION IN RESPONSE TO EDWARDSIELLA
ICTALURI INFECTION
Introduction
Macrophages are important facilitators of Edwardsiella ictaluri infection, where E.
ictaluri can invade, survive, and replicate (1). Opsonization of live E. ictaluri with normal catfish
serum greatly increases E. ictaluri’s uptake into catfish macrophages (1). Once internalized, E.
ictaluri can replicate in spacious vacuoles within the macrophage called Edwardsiella-
containing-vacuoles (ECV) (1). Researchers use macrophages often in experiments indicating
that E. ictaluri survives in macrophages from several tissues, including intestinal macrophages
(2), peritoneal macrophages (3), and head-kidney-derived macrophages (HKDM) (1).
Macrophages are important facilitators of host immune functions, capable of activating and
polarizing in order to aid host defenses (4). Classically, macrophages polarize to the M1 pro-
inflammatory response which promotes killing of invading microbes, or the M2 anti-
inflammatory response which promotes tissue repair (4).
In particular, HKDM are of interest because of their necessity and importance to the
natural disease process, ease of cultivation in laboratory settings, and our understanding of the
dynamics of the host-pathogen interaction (1, 5-7). HKDMs also allow ex vivo modeling of
disease to aid in a better prediction of disease outcome before conducting in vivo assays on
catfish, where host death is usually the end-result.
E. ictaluri has multiple virulence factors that allow it to evade innate immune defense
mechanisms and facilitate replication within macrophages (1, 8-10). Some of the E. ictaluri
virulence factors involved in HKDMs include a urease pathogenicity island (PAI) that encodes
52
an acid activated urease that allows it to modulate pH (11), a Type III secretion system, (12, 13),
and a Type VI secretion system (12). The Thune lab primarily focuses on the role of the E.
ictaluri T3SS in pathogenesis, and, specifically in this study, the involvement of T3SS effector
EseK.
Recent studies in catfish indicate that HKDM may help model immune system
modulation. Russo et al. showed that macrophages exposed to convalescent serum produced
tenfold more reactive oxygen and nitrogen species and killed E. ictaluri better than macrophages
from non-vaccinated fish (14). In another study, Russo et al. found an importance for amino
acids such as glutamine and arginine in increasing the phagocytic capability of macrophages and
subsequent killing of E. ictaluri (7, 14). These findings, together with the common knowledge of
macrophage clearance of intracellular pathogens, suggest a necessity for an M1/ cell-mediated
immune response to clear E. ictaluri in catfish macrophages (14). The literature mentioned
above, however, also strongly indicates that E. ictaluri is very capable of persisting in the naïve
host, particularly in HKDM. Consequently, this experiment aims to address the native response
of HKDMs to infection with E. ictaluri. Based on the literature, we hypothesized that WT
persists and replicates in channel catfish HKDM because it prevents or evades polarizing effects
implemented by HKDMs. Preliminary results and results presented in the previous chapter
suggest that EseK aids WT E. ictaluri in this response. The experimental design for this work
involved using RNA sequence analysis (RNA seq) on WT, ΔeseK, and uninfected HKDM
samples. RNA seq allows for a more in-depth analysis of target samples and a more complete
picture of host-pathogen dynamics (15-21). The predicted regulation of several pathways
indicates a role for M1 polarization. Additionally, we uncovered potential mechanisms for
preventing apoptosis and an effect on initiation of the adaptive immune responses.
53
Methods
Bacterial Growth. Strains used in this study were Edwardsiella ictaluri LADL93-146
isolated in 1993from moribund channel catfish in a natural outbreak of ESC on a commercial
farm, and ΔeseK in E. ictaluri with a deletion of the first 2200 bp, created in the Thune lab. E.
ictaluri strains were grown from frozen stock cultures stored at -80C in 5mL BHI-porcine
(Sigma-Aldrich) overnight (O/N) at 28C with aeration.
Fish Care. Channel catfish egg masses were obtained from a Morehead, Mississippi
catfish farm with no history of ESC outbreaks. The eggs were disinfected with 100 ppm free
iodine and hatched in a closed recirculating system in the specific pathogen-free (SPF)
laboratory at the LSU School of Veterinary Medicine. Fish were reared in systems containing
four, 350 L fiberglass tanks, connected to a 45 L bead filter (Aquaculture Systems
Technologies). Water quality was tested at least three times a week, and the temperature was
constantly monitored to ensure optimal conditions for fish wellness. All experiments were
carried out following protocols approved by from the Institutional Animal Care and Use
Committee and the Inter-Institutional Biological and Recombinant DNA Safety Committee of
Louisiana State University.
HKDM Collection. HKDMs were collected according to the method of Booth et al. 2006
(1). Briefly, fish were euthanized in 1 g/L Tricaine-S (Pentair). Head kidneys were removed,
homogenized through a sterile double stainless-steel mesh tissue sieve (280 and 140 µm) (Sigma
Chemical Co.), and suspended at approximately 1 X107 cells/mL in channel catfish macrophage
medium (CCMM) (22). Five mL per well was added to each well of a 6-well plate (Sigma-
54
Aldrich), and cells were allowed to adhere overnight at 28C in a 5% CO2 atmosphere. Following
this, cells were washed three times in RPMI, re-suspended in 5 mL CCMM and counted.
HKDM Assays. Both WT and ΔeseK were opsonized with normal channel catfish serum
for 30 minutes before being added to 6 well plates containing HKDMs at a multiplicity of
infection (MOI) of 10 bacteria/cell. Plates were then centrifuged at 400x g for 5 minutes to
promote bacterial contact with the cell sheet, then incubated for 30 minutes before a 100 µg/mL
killing dose of gentamicin was added for 1 hour. Following this, HKDMs were washed one time
in RPMI (Sigma-Aldrich) and resuspended in CCMM containing a 1 µg/mL static dose of
gentamicin. Cells were allowed to persist for 5 hours, then washed once with RPMI before
proceeding to RNA extractions. Sampling was performed on three separate occasions according
to the collection and assay protocols.
RNA Extractions. Total RNA extractions were carried out on HKDM samples using
RNAzol® RT Isolation Reagent (Molecular Research Center) in conjunction with the RNA
Clean and Concentrator-5 kit (Zymo Research) following manufacturer protocols. Samples were
resuspended in DEPC-treated H20 (Ambion™). The RNA quality was determined by fragment
analysis using the Agilent Fragment Analyzer (Advanced Technologies, Inc) with the lowest
RNA quality number (RQN) value of 7.4. After fragment analysis, mRNA extractions and runs
were carried out by LSU School of Veterinary Medicine Genelab Core. mRNA was extracted
using the RiboMinus Eukaryote Kit v2 (Ambion™) and was sequenced on an Ion Proton Next-
Generation Sequencer.
Data Analysis. Data was compiled and analyzed by the LSU Center for Computational
Technology using Partek Flow based on researcher input. Unaligned reads were converted to
FASTQ format, trimmed using a quality score and read length (Phred>20; >25bp), then aligned
55
to the Ictalurus punctatus reference genome using STAR (Version 2.6.1d)(23). The reads were
then quantified to the Ictalurus punctatus genome, calculating the fragments per kilobase of
transcript per million aligned reads (FPKM) using the Partek Flow quantification algorithm,
based on the hierarchical model described by Leng et. al (24). Differential analysis between each
macrophage treatment (WT versus uninfected, ΔeseK versus uninfected, and WT versus ΔeseK)
was carried out using Gene Specific Analysis (GSA), and transcripts were selected that had 200
or more total counts with a p-value of 0.2 or less. Pathway analysis was carried out using
Ingenuity Pathway Analysis (IPA), with a q-value cut-off of 0.1, to identify molecular pathways
containing the differentially expressed genes. In IPA, expression analysis allowed the calculation
of the fold change in expression between treatments which were then used to calculate z-scores.
Results
GSA Analysis. Comparisons of the three treatments of samples using GSA analysis
uncovered approximately 45,000 genes, with 2126 genes having p-values of 0.2 or less (Table
3.1). IPA was then carried out to predict the most relevant pathways effected by infection with
WT and ΔeseK compared to uninfected HKDMs. While there were specific genes differentially
regulated between the WT and ΔeseK, none of these were significantly differentially regulated
when analyzed with a q value of 0.1 in the IPA.
Pathway Analysis. To further analyze the data, pathways of interest were examined by
z-score value. Because relatively few differences were observed in the WT versus ΔeseK
treatments, the remaining results focus on pathways significantly changed in the WT compared
to the uninfected HKDMs. Similar results would be expected for ΔeseK compared to uninfected
HKDMs. Approximately 180 pathways were analyzed (Figure 3.1). Several pathways showed a
56
significant difference in regulation. For the sake of this work, the top 40 pathways were
investigated more closely because they had strong combined p-values and z-scores.
57
Table 3.1: Top 50 reads via GSA. P-values and fold-changes given for WT versus uninfected, ΔeseK versus uninfected (Un), and WT
versus ΔeseK.
GENE
SYMBOL Transcript ID
P-value
(WT vs.
Un.)
Fold change
(WT vs. Un.)
P-value
(ΔeseK
vs. Un.)
Fold change
(ΔeseK vs. Un.)
P-value
(WT vs.
ΔeseK)
Fold change (WT
vs. ΔeseK)
JUNB XM_017458253.1 1.83E-07 35.6 1.12E-07 41.9 4.71E-01 -1.2
ENPEP XM_017465049.1 9.93E-07 687.4 8.71E-07 693.0 8.72E-01 -1.0
IER3 XM_017451685.1 1.05E-06 17.5 5.40E-07 21.4 4.12E-01 -1.2
KDM6B XM_017472048.1 1.09E-06 17.9 1.08E-06 17.6 9.96E-01 1.0
LOC108269347 XM_017475170.1 1.65E-06 460.9 1.92E-06 403.7 8.59E-01 1.1
LOC108257234 XM_017454847.1 2.37E-06 4.0 1.54E-06 4.3 6.21E-01 -1.1
LOC108267131 XM_017471106.1 2.46E-06 32.0 1.68E-06 39.5 6.67E-01 -1.2
RNF19B XM_017454608.1 2.60E-06 6.1 1.05E-06 7.1 3.05E-01 -1.2
LOC108269240 XM_017474985.1 2.92E-06 9.7 8.91E-07 12.6 1.87E-01 -1.3
LOC108260811 XM_017461423.1 2.95E-06 21646.6 2.52E-06 23802.9 8.63E-01 -1.1
COBLL1 XM_017470098.1 3.11E-06 330.2 2.85E-06 330.9 9.23E-01 -1.0
NR4A3 XM_017453779.1 3.83E-06 5.1 6.28E-07 7.3 5.60E-02 -1.4
LOC108260305 XM_017460480.1 4.48E-06 8.6 3.76E-06 9.0 8.53E-01 -1.0
TTC13 XM_017449996.1 5.51E-06 124.9 3.44E-06 142.8 6.20E-01 -1.1
NFKBIA XM_017475822.1 5.53E-06 23.6 2.84E-06 28.8 4.81E-01 -1.2
TTC13 XM_017450006.1 5.61E-06 123.2 3.50E-06 140.8 6.20E-01 -1.1
TNFAIP3 XM_017464718.1 6.95E-06 9.1 3.82E-06 10.1 5.37E-01 -1.1
CD82 XM_017478912.1 7.02E-06 8.2 5.00E-06 8.8 7.28E-01 -1.1
ABTB2 XM_017485648.1 7.21E-06 6.2 1.51E-06 9.3 1.12E-01 -1.5
LOC108278857 XM_017492510.1 7.63E-06 30.3 3.42E-06 41.9 4.12E-01 -1.4
AR XM_017459546.1 7.86E-06 37.4 1.28E-05 28.5 6.35E-01 1.3
ITGA2 XM_017488883.1 8.68E-06 16.7 5.28E-06 21.1 6.16E-01 -1.3
LOC108257234 XM_017454838.1 8.70E-06 3.6 3.05E-06 4.2 2.88E-01 -1.2
LOC108269063 XM_017474584.1 9.11E-06 1254.4 6.99E-06 1523.8 7.92E-01 -1.2
RAD17 XM_017451562.1 1.27E-05 246.8 7.42E-06 306.2 6.03E-01 -1.2
DLL1 XM_017463168.1 1.36E-05 130.2 1.28E-05 128.2 9.55E-01 1.0
(table cont’d)
58
Table 3.1 continued
GENE
SYMBOL Transcript ID
P-value
(WT vs.
Un.)
Fold change
(WT vs.
Un.)
P-value
(ΔeseK vs.
Un.)
Fold change
(ΔeseK vs.
Un.)
P-value
(WT vs.
ΔeseK)
Fold change (WT vs.
ΔeseK)
LOC108277114 XM_017489499.1 1.42E-05 146.5 1.82E-05 118.8 8.16E-01 1.2
ACSS2 XM_017486747.1 1.45E-05 7.3 9.35E-06 8.0 6.73E-01 -1.1
LOC108266341 XM_017469480.1 1.45E-05 3.6 6.54E-06 3.9 4.39E-01 -1.1
LOC108270133 XM_017476502.1 1.51E-05 270.7 1.82E-05 227.2 8.62E-01 1.2
NFKBIB XM_017459598.1 1.62E-05 3.6 5.97E-06 4.2 3.39E-01 -1.2
LOC108263482 XM_017464303.1 1.71E-05 260.5 1.71E-05 250.4 9.99E-01 1.0
BCOR XM_017459001.1 1.73E-05 4.4 4.82E-06 5.7 2.26E-01 -1.3
KLF12 XM_017470462.1 1.77E-05 18.1 7.02E-06 24.1 3.81E-01 -1.3
NDUFV3 XM_017470327.1 1.80E-05 67.8 1.69E-05 68.8 9.51E-01 -1.0
NDUFV3 XM_017470326.1 2.08E-05 42.4 1.86E-05 43.1 9.18E-01 -1.0
CBS XM_017458119.1 2.36E-05 16.5 1.04E-05 20.3 4.48E-01 -1.2
CFLAR XM_017469517.1 2.44E-05 14.6 1.10E-05 17.5 4.61E-01 -1.2
LOC108265972 XM_017468874.1 2.47E-05 18.6 1.35E-05 21.7 5.76E-01 -1.2
DOPEY2 XM_017469589.1 2.61E-05 3.5 8.17E-06 4.3 2.86E-01 -1.2
LOC108255781 XM_017451987.1 3.22E-05 7.8 7.88E-06 11.8 2.06E-01 -1.5
ATG4D XM_017457236.1 3.28E-05 3.2 1.68E-05 3.4 5.47E-01 -1.1
CD82 XM_017478916.1 3.28E-05 8.6 1.93E-05 9.9 6.33E-01 -1.2
PTGIS XM_017480375.1 3.59E-05 13.3 3.29E-05 13.5 9.40E-01 -1.0
XKR7 XM_017486463.1 3.72E-05 36.3 3.91E-05 35.9 9.65E-01 1.0
LOC108269063 XM_017474585.1 3.74E-05 97.4 2.43E-05 116.7 7.03E-01 -1.2
LOC108257234 XM_017454818.1 3.99E-05 3.2 1.97E-05 3.5 5.35E-01 -1.1
LOC108265925 XM_017468777.1 4.03E-05 4.3 1.65E-05 5.0 4.31E-01 -1.2
RAI14 XM_017492770.1 4.15E-05 3.3 1.21E-05 4.0 2.78E-01 -1.2
MAP3K1 XM_017489827.1 4.37E-05 3.6 1.00E-05 4.4 1.98E-01 -1.2
59
Figure 3.1: Top 40 pathways according to overall -log(p-value) (y- axis), differentially regulated in WT compared to uninfected
HKDMs. Intensity of color indicate positive (orange), negative (blue), or no change (white) in z-score.
60
Notable pathways within the top 40 which are predicted to be upregulated in the WT compared
to uninfected HKDMs were both TNFR1 and TNFR2 signaling, Acute Phase Response
signaling, IL-6 signaling, P13K/AKT signaling (Figure 3.2), Production of Nitric Oxide and
Reactive Oxygen Species in Macrophages (which was not indicated in pathway analysis), IL-15
signaling, INOS signaling, NF-κB Activation by Viruses (Figure 3.2, Table 3.2), IL-1 signaling,
and Tec Kinase signaling.
Notable Pathways within the top 40 which are predicated to be downregulated in the WT
compared to uninfected HKDMs were Death Receptor signaling (Figure 3.3), CD40 signaling,
and PPAR signaling (Figure 3.1, Table 3.3).
Discussion
The RNA-seq data generated in this study has yielded an abundance of valuable information,
including several genes that exhibited high degrees of differential expression that were not
within the previously prescribed pathways, and will require a great deal of further investigation.
Because no pathways were predicted as differentially regulated between the WT and ΔeseK
infected HKDMs, we concluded that EseK has no bearing on transcription under these
parameters. Therefore, analysis of this work focused on WT compared to uninfected HKDMs.
The differential regulation of several important pathways and their related transcripts in response
to E. ictaluri infection have implications in M1 polarization. Upregulation of the iNOS pathway
is a classical indicator of M1 activation in macrophages (25, 26). Likewise, the upregulation of
both the acute phase response pathway (27), and NF-kB viral pathway have indications in M1
polarization. Further support for M1 polarization comes from the predicted downregulation of
the proliferator receptor (PPAR) signaling pathway (4). Unlike the other pathways, the PPARγ
61
Table 3.2 Top upregulated pathways Predicted by IPA showing the top predicted genes per pathway, and its corresponding expression
value in WT compared to uninfected HKDMs, the false discovery rate (q- value), and the fold change between the WT and uninfected
HKDMs. IPA also indicated the expected regulation, location, and type of molecule per gene.
Symbol Gene Name p-value q-value Fold Change Expected Location Type(s)
TNFR1 and TNFR2 Signaling Pathways
BIRC2
baculoviral IAP repeat
containing 2 6.48E-04 7.22E-02 4.3
Down Cytoplasm enzyme
MAP3K1
mitogen-activated protein
kinase kinase kinase 1 4.37E-05 2.12E-02 3.6
Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha 5.53E-06 9.52E-03 23.6
Up Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta 1.62E-05 1.31E-02 3.6
Up Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon 2.61E-04 4.67E-02 3.5
Up Nucleus
transcription
regulator
TANK
TRAF family member
associated NFKB activator 1.03E-04 3.02E-02 4.2
Down Cytoplasm other
TNFAIP3 TNF alpha induced protein 3 6.95E-06 1.04E-02 9.1 Nucleus enzyme
Acute Phase Response Signaling
IL1B interleukin 1 beta 5.31E-05 2.32E-02 35.4
Up
Extracellul
ar Space cytokine
JAK2 Janus kinase 2 2.24E-04 4.31E-02 4.5 Up Cytoplasm kinase
MAP3K1
mitogen-activated protein
kinase kinase kinase 1 4.37E-05 2.12E-02 3.6
Up Cytoplasm kinase
MAP3K5
mitogen-activated protein
kinase kinase kinase 5 1.20E-04 3.17E-02 4.3
Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
(table cont’d)
62
Table 3.2 continued
Symbol Gene Name p-value q-value Fold Change Expected Location Type(s)
NFKBIA NFKB inhibitor alpha 5.53E-06 9.52E-03 23.6
Up Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta 1.62E-05 1.31E-02 3.6
Down Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon 2.61E-04 4.67E-02 3.5
Down Nucleus
transcription
regulator
SHC1 SHC adaptor protein 1 9.37E-04 8.91E-02 2.5 Up Cytoplasm other
SOCS3
suppressor of cytokine
signaling 3 5.01E-05 2.24E-02 5.4
Down Cytoplasm phosphatase
STAT3
signal transducer and
activator of transcription 3 9.23E-04 8.84E-02 2.2
Up Nucleus
transcription
regulator
IL-6 Signaling
IL1B interleukin 1 beta 5.31E-05 2.32E-02 35.4
Up
Extracellul
ar Space cytokine
JAK2 Janus kinase 2 2.24E-04 4.31E-02 4.5 Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha 5.53E-06 9.52E-03 23.6
Up Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta 1.62E-05 1.31E-02 3.6
Up Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon 2.61E-04 4.67E-02 3.5
Up Nucleus
transcription
regulator
SHC1 SHC adaptor protein 1 9.37E-04 8.91E-02 2.5 Up Cytoplasm other
SOCS3
suppressor of cytokine
signaling 3 5.01E-05 2.24E-02 5.4
Down Cytoplasm phosphatase
STAT3
signal transducer and
activator of transcription 3 9.23E-04 8.84E-02 2.2
Up Nucleus
transcription
regulator (table cont’d)
63
Table 3.2 continued
Symbol Gene Name p-value q-value Fold Change Expected Location Type(s)
NF-kB Virus Pathway
ITGA2 integrin subunit alpha 2 8.68E-06 1.06E-02 16.7
Up
Plasma
Membrane
transmembrane
receptor
MAP3K1
mitogen-activated protein
kinase kinase kinase 1 4.37E-05 2.12E-02 3.6
Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha 5.53E-06 9.52E-03 23.6
Up Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta 1.62E-05 1.31E-02 3.6
Up Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon 2.61E-04 4.67E-02 3.5
Up Nucleus
transcription
regulator
P13K/AKT Pathway
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha 5.53E-06 9.52E-03 23.6
Up Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta 1.62E-05 1.31E-02 3.6
Up Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon 2.61E-04 4.67E-02 3.5
Up Nucleus
transcription
regulator
PIK3AP1
phosphoinositide-3-kinase
adaptor protein 1 6.30E-04 7.13E-02 3.2
Up Cytoplasm other
PLEKHA1
pleckstrin homology domain
containing A1 2.75E-04 4.73E-02 3.4
Cytoplasm other
SYK
spleen associated tyrosine
kinase 9.24E-04 8.84E-02 2.5
Up Cytoplasm kinase (table cont’d)
64
Table 3.2 continued
Symbol Gene Name p-value q-value Fold Change Expected Location Type(s)
IL-15 Pathway
IL2RG
interleukin 2 receptor
subunit gamma 3.22E-04 5.16E-02 3.1
Up
Plasma
Membrane
transmembrane
receptor
JAK2 Janus kinase 2 2.24E-04 4.31E-02 4.5 Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
SHC1 SHC adaptor protein 1 9.37E-04 8.91E-02 2.5 Up Cytoplasm other
STAT3
signal transducer and
activator of transcription 3 9.23E-04 8.84E-02 2.2
Up Nucleus
transcription
regulator
SYK
spleen associated tyrosine
kinase 9.24E-04 8.84E-02 2.5
Up Cytoplasm kinase
iNOS Signaling Pathway
JAK2 Janus kinase 2 2.24E-04 4.31E-02 4.5 Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha 5.53E-06 9.52E-03 23.6
Up Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta 1.62E-05 1.31E-02 3.6
Up Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon 2.61E-04 4.67E-02 3.5
Up Nucleus
transcription
regulator
IL-1 Signaling Pathway
GNAI2 G protein subunit alpha i2 7.49E-04 7.83E-02 2.3
Plasma
Membrane enzyme
MAP3K1
mitogen-activated protein
kinase kinase kinase 1 4.37E-05 2.12E-02 3.6
Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
(table cont’d)
65
Table 3.2 continued
Symbol Gene Name p-value q-value Fold Change Expected Location Type(s)
NFKBIA NFKB inhibitor alpha 5.53E-06 9.52E-03 23.6
Up Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta 1.62E-05 1.31E-02 3.6
Up Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon 2.61E-04 4.67E-02 3.5
Up Nucleus
transcription
regulator
GNAI2 G protein subunit alpha i2 7.49E-04 7.83E-02 2.3
Plasma
Membrane enzyme
Tec Kinase Signaling
ITGA2 integrin subunit alpha 2 8.68E-06 1.06E-02 16.7
Up
Plasma
Membrane
transmembrane
receptor
JAK2 Janus kinase 2 2.24E-04 4.31E-02 4.5 Up Cytoplasm kinase
NFKB2
nuclear factor kappa B
subunit 2 5.38E-05 2.33E-02 4.8
Up Nucleus
transcription
regulator
RHOQ
ras homolog family member
Q 4.87E-04 6.34E-02 3.2
Up
Plasma
Membrane enzyme
RHOT2
ras homolog family member
T2 1.02E-03 9.22E-02 5.9
Up Cytoplasm enzyme
STAT3
signal transducer and
activator of transcription 3 9.23E-04 8.84E-02 2.2
Up Nucleus
transcription
regulator
66
Figure 3.2: Combined NF-κB virus and P13K/AKT signaling pathway. Molecules predicted to
be upregulated in WT infected HKDM compared to uninfected HKDMs appear in Red/pink. IPA
predicts that integrin and cytokine activation leads to AKT, which activates the COX kinase,
activating the IKK kinase, which in turn activates the NF-κB, IκB complex, ultimately leading to
cell growth and survival.
67
Table 3.3 Top Downregulated Pathways predicted by IPA showing the top predicted genes per pathway, and its corresponding
expression value in WT compared to uninfected HKDMs, the false discovery rate (q- value), and the fold change between the WT and
uninfected HKDMs. IPA also indicated the expected regulation, location, and type of molecule per gene.
Symbol Gene Name p-value q-value
Fold
Change Expected Location Type(s)
Death Cell Receptor Signaling Pathway
BIRC2 baculoviral IAP repeat containing 2
6.48E-
04 7.22E-02 4.3 Down Cytoplasm enzyme
CFLAR
CASP8 and FADD like apoptosis
regulator
2.44E-
05 1.57E-02 14.6 Down Cytoplasm other
MAP3K5
mitogen-activated protein kinase
kinase kinase 5
1.20E-
04 3.17E-02 4.3 Up Cytoplasm kinase
NFKB2 nuclear factor kappa B subunit 2
5.38E-
05 2.33E-02 4.7 Up Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha
5.53E-
06 9.52E-03 23.5 Down Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta
1.62E-
05 1.31E-02 3.5 Down Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon
2.61E-
04 4.67E-02 3.5 Down Nucleus
transcription
regulator
TANK
TRAF family member associated
NFKB activator
1.03E-
04 3.02E-02 4.2 Cytoplasm other
CD40 Signaling Pathway
NFKB2 nuclear factor kappa B subunit 2
5.38E-
05 2.33E-02 4.7 Up Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha
5.53E-
06 9.52E-03 23.5 Down Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta
1.62E-
05 1.31E-02 3.5 Down Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon
2.61E-
04 4.67E-02 3.5 Down Nucleus
transcription
regulator
(table cont’d)
68
Table 3.3 continued
Symbol Gene Name p-value q-value
Fold
Change Expected Location Type(s)
STAT3
signal transducer and activator of
transcription 3
9.23E-
04 8.84E-02 2.2 Up Nucleus
transcription
regulator
TANK
TRAF family member associated
NFKB activator
1.03E-
04 3.02E-02 4.2 Down Cytoplasm other
TNFAIP3 TNF alpha induced protein 3
6.95E-
06 1.04E-02 9.0 Down Nucleus enzyme
PPAR Signaling Pathway
IL1B interleukin 1 beta
5.31E-
05 2.32E-02 35.3 Down
Extracellula
r Space cytokine
NFKB2 nuclear factor kappa B subunit 2
5.38E-
05 2.33E-02 4.7 Down Nucleus
transcription
regulator
NFKBIA NFKB inhibitor alpha
5.53E-
06 9.52E-03 23.5 Down Cytoplasm
transcription
regulator
NFKBIB NFKB inhibitor beta
1.62E-
05 1.31E-02 3.5 Down Nucleus
transcription
regulator
NFKBIE NFKB inhibitor epsilon
2.61E-
04 4.67E-02 3.5 Down Nucleus
transcription
regulator
SHC1 SHC adaptor protein 1
9.37E-
04 8.91E-02 2.4 Down Cytoplasm other
69
Figure 3.3: Death Receptor Signaling Pathway. Molecules predicted to be upregulated in WT
infected HKDM compared to uninfected HKDM appear in Red/pink. IPA predicts that ultimately
NF-κB complex production leads to the production of the XIAP inhibitory complex preventing
cell death through apoptosis.
transcript is important for macrophage polarization to the M2 phenotype, and the absence of
PPARγ has been shown to cause M1 polarization, so the downregulation of this pathway would
suggest M1 polarization (4). Although some of these pathways can be indicated in both M1 and
M2 response, a recent study looking at differences in M1 and M2 activation as it relates to
classical and alternative activation in mouse bone marrow-derived macrophages supports our
70
findings for the M1/ classical activation phenotype (27). Just as in their study, we saw activation
of the previously mentioned pathways in response to E. ictaluri as well as the TNFR1/2
pathways, IL-1 pathway, IL-6 pathway and PI3K/AKT pathway (27). Conversely, it is important
to point out that some of these pathways have additional indications towards the M2 phenotype
such as the upregulation of the PI3K/AKT pathway (28), and may point to an attempt to maintain
a neutral regulation of the macrophage as these pathways tend to lean more towards an M2
polarization response.
The transcripts belonging to the NF-κB family, NFKB2, and inhibitor family, NFKBIA,
NFKBIB, and NFKBIE, were highly expressed and indicated in most IPA analyses, favoring
both the likelihood of an M1 phenotype, and the potential suppression of apoptosis in favor of
cell survival. Activation of NF-κB family proteins, including NFKB2, is primarily initiated by
the upstream IκB kinase (IKK) complex. This complex, along with the IκB family of inhibitors,
such as NFKBIA, NFKBIB, and NFKBIE, which transcribe 3 of the 5 IκB proteins, allow the
modulation of inflammatory responses due to infection (29-31). A study using channel catfish
mucosal tissues identified 13 NF-κB related genes, and determined that all NF-κB genes existed
as a single copy with the exception of NFKBIA (29). This is of interest because NFKBIA
exhibited the greatest fold change out of the NF-κB family in response to E. ictaluri infection.
Two studies that collected data on catfish mucosal tissue in response to F. columnare
infection (19, 29), found that, in general, NF-κB was induced in all tissues, but different genes
within the family were significantly regulated suggesting variability in NF-κB activation in
various tissue (29). They also noticed this difference in resistant and susceptible catfish (29). The
NF-κB pathway can be initiated by several upstream modulators including LPS activation of
TLRs (32). It is likely that the LPS of E. ictaluri is involved with the downstream activation of
71
the NF-κB pathway, however, the current analysis has not provided an obvious answer. While
TLRs are known to activate the NF-κB pathway, only small fold changes in some TLRs were
observed in the GSA data in the course of this experiment (29). This is consistent with other
studies that have indicated modest activation of TLRs in catfish tissues in response to both E.
ictaluri and F. columnare infections (17-19). Sun et al. suggested that by comparison, more
highly expressed lectins and non-traditional immune factors such as MFAP4 could be more
important for this recognition (19). Further data mining will be required to uncover which
TLR’s, or other PRR’s, may be involved with induced signaling.
Another possible answer this analysis uncovered is the fate of the HKDMs after E.
ictaluri infection. Classically, apoptosis is both a normally occurring event to maintain cell
populations, as well as a defense mechanism employed in response to damaged or diseased cells
(33, 34). However, the strong regulation of NF-κB and downregulation of two other important
pathways in the IPA analysis, the Tec kinase signaling pathway and the death receptor pathway,
indicate that HKDMs are prevented from undergoing apoptosis. In the context of macrophages,
Tec family kinases, whose pathway was upregulated in this study, have been shown to promote
macrophage survival (35). TNFR1 also contains a death domain and is involved in apoptosis,
although this process is typically suppressed by NF-κB induced expression of FLIP and receptor
pathway, and the production of FLIP in the TNFR1 pathway would favor production of NF-κB
(36). Additionally, pathway analysis of the PI3K/AKT and NF-κB pathway indicates that NF-κB
production ultimately leads to cell growth and survival.
Indications from several pathways suggest that HKDM favor autophagy, which is often
involved in routine maintenance and phagocytosis (37, 38). The upregulation of the IL-1
signaling pathway, of which IL-1β is highly expressed, and the iNOS pathway also indicate
72
autophagy is more likely (39). NF-κB is also implicated in these pathways and can regulate
autophagy, and is typically involved with cell survival, proliferation, inflammatory responses,
and angiogenesis by activating several cytokines including IL-6 (39). Previous reports have
shown the ability of E. ictaluri to survive and replicate in ECV within HKDM (1), so while it
possible that the host eventually overcomes bacterial evasion, it seems more likely that E.
ictaluri is unhindered by the autophagic environment of the HKDM, like many other bacteria
(37).
In a related study looking at ECV surface markers, Dubytska and Thune (Submitted)
found that WT E. ictaluri suppresses apoptosis and allows limited recruitment of the autophagy
marker LC3 on WT containing ECVs along with limited phosphorylation of LC3-I to LC3-II.
This further suggests that E. ictaluri may be allowing the HKDM to move towards an autophagic
response but is capable of avoiding degradation by this pathway.
The current analysis also uncovered interesting possibilities regarding the fate of host
signaling in response to bacterial infection. The CD40 pathway in the macrophage is
downregulated in response to E. ictaluri infection. CD40 is a key molecule involved with
activating T cells, so this suggests a limited ability to fully mature and activate T-cells in the
presence of E. ictaluri (40, 41).
In conclusion, it appears that strong regulation of NK-κB family members drive an M1
phenotype in HKDM in response to E. ictaluri infection, and that this also drives the cell to favor
autophagy, possibly allowing the bacteria to survive and replicate longer. In addition,
downregulation of the CD40 pathway could have interesting ramifications on the fate of T cell
dependent immune responses. This observation will be aided by deeper analysis of the current
73
data as well as in vivo experimentation to better elucidate differences in early adaptive cell-
mediated immunity of the host compared to the two infected treatments.
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41. Lagos LX, Iliev DB, Helland R, Rosemblatt M, Jorgensen JB. 2012. CD40L--a
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78
CHAPTER 4. EDWARDSIALLA ICTALURI EVADES T CELL RESPONSES
IN THE CHANNEL CATFISH
Introduction
Edwardsiella ictaluri is a gram-negative facultative intracellular bacterium and the
causative agent of enteric septicemia in the channel catfish (ESC). Reports indicate that ESC
infects several fish species, including tilapia, zebrafish, barbs, and other catfish species (1), but is
of economic significance in the catfish industry, where reported outbreaks on 19.3% of
fry/fingerling operations, 40.4% of fingerling operations, and 36.6% of operations producing
food size fish (2). In the catfish host, ESC mainly affects the intestine, but can also be isolated
from the head kidney, brain, and liver, and is characterized by internal and external physical and
physiologic changes, including ulcerations on the skin and swelling of the abdomen (1).
Previous research indicated that E. ictaluri persists in catfish due to an ability to evade
and manipulate the immune response, but little research has been conducted on the function of
CMI responses in naïve fish. In mammals, the immune system is extremely complex,
encompassing many different cell types and regulatory components. Antigen presentation to T
cells is an important cell-mediated linkage between the innate and adaptive arms of immunity
(3). One example of this is antigen presentation by antigen-presenting cells (APCs) using the
Major Histocompatibility Complex class II (MHC class II) carrying foreign peptides, which are
recognized by CD4 T cells (3). Antigen presentation is often considered a major initiator of the
adaptive immune response and is a function of APCs, such as dendritic cells, macrophages, and
B cells (4). Our understanding of fish immunity has increased over the years and revealed that
the teleost immune system is highly similar to mammals, with innate, adaptive, humoral, and
cell-mediated components (5). Teleost immune systems include many of the same white blood
79
cell types as mammals, such as macrophages, neutrophils, dendritic cells, B cells, CD8 T cells,
and CD4 T cells (6-12). Teleosts also have a vast array of cytokines, and many carry out the
same or similar functions to their mammalian counterparts (13-15).
Recent work showed that the E. ictaluri T3SS effector EseK binds to the hosts CD74
protein, (see chapter 2) (16). This is of potential interest because CD74 plays several important
roles in immune related pathways, such as binding to MHC class II and preventing endogenous
protein binding while allowing MHC to assemble, acting as the binding ligand for macrophage
migration inhibitory factor (MIF) and aiding in cross-presentation to MHC class I (17-19).
Therefore, this experiment hoped to address the actual response of naïve catfish to E. ictaluri
infection using both the WT and the EseK null strain, ΔeseK.
The nCounter® Analysis system boasts a highly sensitive, accurate, reproducible
platform that introduces less bias from amplification steps required in RNA sequencing and
qRT-PCR counterpart technologies (20-22). Instead, probe pairs consisting of a Reporter probe
and a Capture probe containing barcode sequences unique to each target of interest are directly
hybridized to mRNA, which also allows multiple targets per sample. In a study by Bouzas et al.,
additional positive respiratory syncytial virus (RSV) samples were detected by this platform that
were not detected by RT-PCR methods, a result that the researchers believed to be genuine (20).
Because the nCounter® system hybridizes a probe directly to mRNA, it increases accuracy by
removing bias associated with cDNA conversion (22). A study by Chen et al. using formalin-
fixed paraffin-embedded (FFPE) samples found that technical replicates were highly
reproducible, with a correlation of 0.983. This platform uses low amounts of total RNA (21, 22)
and can accurately detect mRNA expression, even in highly degraded RNA samples (23). Lastly,
this system occupies a niche between conventional RNA-seq and qRT-PCR methods where up to
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800 probes can be targeted to each RNA sample, using a multitude of samples per experiment
(24).
In addition, flow cytometry allowed for identification of T cell populations. Flow
cytometry is a useful tool for determining individual cell populations from a heterogenous
population for downstream assays. While a limited number of antibodies specific to channel
catfish proteins exist, we were unable to procure one specific to all T cells at the time of this
experiment. Therefore, a commercially available CD3ε T cell marker was used that preliminary
experiments showed was effective for targeting catfish CD3ε.
The goal of these experiments is to better characterize the role of the WT in the host
immune response and to determine the potential involvement of EseK in the host immune
response. A combination of transcriptional analysis with nCounter® and flow cytometry were
used to determine that E. ictaluri suppresses certain T cell immune responses, which likely
allows it to persist in the host.
Methods
Bacterial Strains. Bacterial strains used in this study were wild-type (WT) Edwardsiella
ictaluri LADL 93-146, isolated in 1993 from moribund channel catfish in a natural outbreak of
ESC on a commercial farm, and ΔeseK, a mutated strain of E. ictaluri 93-146 containing a
deletion of the first 2200 bp of EseK. Strains were grown from -80C frozen back cultures in 5mL
BHI-porcine (Sigma-Aldrich) overnight (O/N) at 28C with aeration. These starter cultures were
used for downstream assays.
Fish Care. Channel catfish eggs obtained from a Morehead Mississippi catfish farm with
no history of ESC outbreaks were disinfected with 100 ppm free iodine and hatched in a closed
recirculating system in the specific pathogen-free (SPF) laboratory at the LSU School of
81
Veterinary Medicine. Fish were reared in systems containing four, 350 L fiberglass tanks,
connected to a 45 L bead filter (Aquaculture Systems Technologies). Water quality was tested at
least three times a week, and the temperature was constantly monitored to ensure optimal
conditions for fish wellness. Fish weighing approximately 40g were moved to challenge tanks at
25 fish per 20 L flow-through tank. Catfish were fed 2% body weight every other day and
allowed to acclimate 28 days before inoculation (25). All experiments were carried out following
protocols approved by the Institutional Animal Care and Use Committee and the Inter-
Institutional Biological and Recombinant DNA Safety Committee of Louisiana State University.
Immersion Assays. Starter cultures of WT and the ΔeseK strain were used to inoculate
400 mL of porcine-BHI per 2 L flask at 28C, and cultures were allowed to incubate until each
culture reached an OD600 1.9, reflecting a concentration of 1 X1010 colony-forming unit’s (CFU)
per mL. The culture was then diluted as required per treatment dose for the inoculation of catfish.
The bacterial concentration was subsequently verified by drop plating using ten-fold serial
dilutions in triplicate on Trypticase Soy Agar supplemented with 5% defibrinated sheep blood
(BA) (26).
Fish Sampling. Fish were anesthetized in 100 mg/L Tricaine S (Pentair). Blood was
collected by caudal vein puncture into K3 EDTA tubes (Becton, Dickinson and Company) and
processed for peripheral blood leukocytes (PBLs). Fish were then euthanized in 1 g/L Tricaine S
for tissue collection. One fish per tank was collected per day.
PBL Collection. PBLs were collected by gradient centrifugation as modified from Miller
et al. (26). Briefly, blood was mixed equal parts with modified PBS (mPBS) consisting of 9
parts 1XPBS:1part H20, with 2% heat inactivated, filter-sterilized channel catfish serum. The
mixture was layered over a Lymphoprep (Stem Cell Technologies) density gradient with a
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specific density of 1.077 g/mL. Centrifugation was carried out at 800x g (accuSpin™ 3R, Fisher
Scientific) for 30 minutes at room temperature. The buffy layer was then removed and washed
twice in mPBS followed by centrifugation at 800x g for 8 minutes.
For nCounter experiments, flash lysis was used following the final wash step to remove residual
red blood cells. PBLs were centrifuged at 800x g for 1 min in distilled water (28). The
supernatant was removed, and cells were immediately placed in RNAzol for RNA processing.
Tissue Collection. Head Kidney (HK) tissue was aseptically removed from sampled
catfish. The HK was dissected into 3 portions and weighed for the nCounter® experiment. One
portion was used to determine CFU per gram of tissue, one portion was used for RNA extraction,
and one portion was flash-frozen using liquid nitrogen and stored at -80C. For flow cytometry,
HK was weighed and used for CFU counts.
CFU counts. Bacterial counts were quantified per each HK sample by homogenizing
weighed HK tissue in sterile saline using a bead beater (Bullet Blender 24, Next Advance Inc,) at
a speed setting of 8 for 4 minutes. Ten-fold serial dilutions were prepared of each homogenate,
plated in triplicate onto BA plates, and grown at 28C for 48 hours. Colony counts per gram of
tissue were recorded.
RNA Extractions. Total RNA extractions were carried out on HK and PBL samples
using RNAzol® RT Isolation Reagent (Molecular Research Center) in conjunction with the RNA
Clean and Concentrator-5 Kit (Zymo Research) following manufacturer protocols. Samples were
re-suspended in DEPC-treated H20 (Ambion™). The HK tissue had an additional initial step of
homogenization, which was carried out by adding HK to 1 mL of RNAzol RT and homogenizing
on a bead beater (Bullet Blender 24, Next Advance Inc,) at a speed setting of 5 for 2 minutes. All
RNA samples were quantified on a NanoDrop (Thermo Fisher Scientific), and the 260/280 value
83
was taken to determine that samples had a value of approximately 1.9 or greater to establish the
purity of samples. Additionally, a random selection of RNA samples were tested for RNA
quality using the Agilent Fragment Analyzer (Advanced Technologies, Inc).
Probe Creation. Total RNA of each sample was used for hybridization of catfish mRNA
to probes (Appendix 2, Table 1) created as a custom codeset (29), designed by NanoString
Technologies. nCounter® analysis was carried out at the LSU Health Science Center, New
Orleans, LA. Briefly, 15 ng of each sample was mixed with each probe as well as eight positive
spike-in controls, and six negative spike-in controls.
Flow Cytometry. For flow cytometry, PBLs were counted on a Countess automated cell
counter (Invitrogen) and approximately 1 X 106 PBL cells were isolated for use. PBLs were
blocked with Fc Blocker (anti CD16/CD32), fixed with 4% formaldehyde, and permeabilized
with 0.5% saponin. Staining was performed using 2 µg human anti-CD3ε (Novus), with 1:200
anti-human conjugated FITC. Cells were analyzed on a FACSCalibur flow-cytometer (Becton-
Dickinson,) and gating was performed using forward and side scatter for separation of size and
internal granularity (Figure 4.1). A gate was then set over lymphocyte populations from which
the percentage of CD3+ cells were identified.
Analysis and Statistics. Raw nCounter data was analyzed using nSolver Analysis
Software 4.0.70 (NanoString Technologies). Positive spike-in controls were used to correct
technical variation, and negative spike-in controls were used to correct for background variation.
Codeset content normalization was carried out using three fish housekeeping genes (B2M,
EEF1A, and ACTB). Seven of the 192 samples were excluded. Three samples were excluded
from analysis because there were no colonies recovered from BA plates (D2-T7, D6-T7, and D7-
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T9). One sample, out of 192, failed to run correctly before analysis (D6-T12H). Additionally,
samples that
were flagged by the software were removed (D2-T12P, D5-T5P, and D5-T10P). After sample
exclusion, at least 3 samples per treatment group per day for analysis remained. Fish infected
with WT, ΔeseK, or BHI-Sham were sampled at time 0 and for 7 days following infection, and
gene function was analyzed in HK tissue and PBLs. Using PRISM, GraphPad version 5.00.288,
a two-way ANOVA was performed with Tukey’s posthoc test and confidence interval of 95% to
determine significance among treatments per day. Flow cytometry data were gated and analyzed
using FlowJo™ Software version 10.6.1 (Becton, Dickinson and Company). Using PRISM,
GraphPad version 5.00.288, a two-way ANOVA was performed with Tukey’s posthoc test and
confidence interval of 95% to determine significance among gate types and treatments per day.
Figure 4.1: Representation of gating strategy with Day 0 samples. Using FlowJo, gates were
drawn over lymphoid and myeloid/precursor populations using FSC versus SSC. Lymphoid
populations were then analyzed for CD3ε+ cells based on FITC fluorescence. Percentage of
CD3ε + cells were calculated based on comparison to secondary antibody control per each day
(as seen above).
85
Results
Because WT and ΔeseK did not show significant differences between one another during
the course of this experiment, the focus will be on the WT versus the uninfected catfish. Graphs
still include the ΔeseK treatment for reference.
Head Kidney: CD74/MIF (Figure 4.2). CD74 was downregulated compared to the
Sham from days 2 through 7 in HK samples treated with WT. The inverse of this pattern was
observed in MIF expression of HK samples treated with WT, where upregulation was observed
from days 2 through 7.
Figure 4.2: CD74 and MIF expression in HK per treatment graphed by the log2 transformation of
normalized RNA counts per day. Letters denote significant differences among treatments within
each day, identified by two-way ANOVA with a CI of 95%.
T Cell Markers (Figure 4.3). In HK samples treated with WT, CD3 was downregulated
compared to the Sham on day 7. This same trend of latent downregulation was observed in
CD4_1 expression, where HK samples treated with WT were downregulated compared to the
Sham on day 7. More significantly, CD4_2 expression in HK samples treated with WT was
downregulated on days 4 through 7.
86
CD8α_1 followed a similar pattern to CD3 and CD4, where downregulation was
observed on days 6 and 7 in WT treated HK samples compared to the Sham. However, CD8α_2
was downregulated on day 7 in WT treated HK samples compared to the Sham.
CD40L followed a similar pattern to the other T cell markers, where downregulation was
observed on days 6 and 7 in both WT treated HK samples compared to the Sham.
Cytokine Indicators (Figure 4.4). IL-8_2 was upregulated in HK samples infected with
WT compared to Sham on days 2 through 5, but no difference in IL-8_1 expression was
observed between treatments. IL-8_3 did not amplify.
In HK samples treated with WT, IFN-γ was upregulated compared to the Sham on days 2
and 5, and TGF-β1 was downregulated on days 2 and 5 in WT treated HK samples compared to
the Sham.
Similarly, IL-1β was upregulated in HK samples infected with WT compared to Sham on
days 2 and 3. In addition, IL-6 was upregulated in HK samples infected with WT compared to
Sham on day 2. No differences in the expression of IL-10, TNF-α, or IL-17A were observed
between WT and Sham.
87
Figure 4.3: Expression of T cell Markers in HK per treatment graphed by the log2 transformation of normalized RNA counts per day.
Letters denote significant differences among treatments within each day, identified by two-way ANOVA with a CI of 95%.
88
Figure 4.4: Expression of other cytokine indicators in HK per treatment graphed by the log2 transformation of normalized RNA
counts per day. Letters denote significant differences among treatments within each day, identified by two-way ANOVA with a CI of
95%.
89
PBL: CD74/MIF (Figure 4.5). CD74 was downregulated compared to the Sham on days
2, and 5 through 7 in PBL samples treated with WT. The inverse of this pattern was observed in
MIF expression of PBL samples treated with WT, where upregulation was observed from days 3
through 7
Figure 4.5: CD74 and MIF expression in PBL per treatment graphed by the log2 transformation
of normalized RNA counts per day. Letters denote significant differences among treatments
within each day, identified by two-way ANOVA with a CI of 95%.
T-Cell Markers (Figure 4.6). In PBL samples, no difference in CD3 expression was
observed between among any treatment. In contrast to HK expression, no difference in CD4_2
expression was observed between treatments. CD4_1 did not amplify.
However, CD8α_1 upregulation was observed on day 5 in WT treated PBL samples
compared to the Sham. Similarly, CD8α_1 was upregulated on day 6 in WT treated HK samples
compared to the Sham. Following the pattern observed in HK, CD40L expression was
downregulation on days 0, and 5 through 7 in WT treated PBL samples compared to the Sham.
90
Figure 4.6: Expression of T cell markers in PBL per treatment graphed by the log2 transformation of normalized RNA counts per day.
Letters denote significant differences among treatments within each day, identified by two-way ANOVA with a CI of 95%.
91
Cytokine Indicators (Figure 4.7). No difference was observed in IL-8_1 expression
between WT and Sham. Following the same regulation patterns in HK, IL-8_2 was upregulated
in PBL samples infected with WT compared to Sham on day 7.
TGF-β1 downregulation was observed on days 6 and 7 in WT infected PBL samples
compared to the Sham. IL-10 expression in PBL samples treated with WT, were upregulated
compared to the Sham on days 2 and 7. IL-17A expression in PBL samples treated with WT,
were upregulated compared to the Sham on days 2 and 5. TNF-α expression in PBL samples
treated with WT, were downregulated compared to the Sham on day 4.
No difference in the expression of IL-6 or IFN-γ was observed between WT and Sham in
PBL samples.
Flow Cytometry. CD3ε detection in PBL populations from WT, ΔeseK, and uninfected
fish did not show any statistically significant changes in population number among treatments
per day, suggesting that overall T cell populations are not proliferating (Figure 4.8, Table 4.2).
Discussion
This work characterized cell-mediated responses to WT infection. We examined
components of the catfish immune system to gain insight into naïve catfish immune responses
generated to E. ictaluri infection, with a special interest in cell mediated responses. The
secondary goal focused on determining if these responses were specific to hematopoietic tissue
such as the HK, or if they were also present as part of a systemic response. The results showed
that CD74 and CD40L were significantly downregulated across multiple days in all bacterial
samples in all tissues compared to the Sham. Similarly, MIF was upregulated in all infected
tissue compared to the Sham, although this regulation was less pronounced in ΔeseK infected
PBL tissue. In addition, expression of some genes were robust but only present in one
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Figure 4.7: Expression of other cytokine indicators in PBL per treatment graphed by the log2 transformation of normalized RNA
counts per day. Letters denote significant differences among treatments within each day, identified by two-way ANOVA with a CI of
95%.
93
Figure 4.8: Percentage of CD3e+ lymphocytes grouped by treatment with SEM. Percentages
were calculated by gating CD3 populations based on F1 scatter and subtracted from respective
secondary per respective day.
tissue type, such as a decrease in the expression of T cell related transcripts and IL-8 in HK.
Likewise, TGF-β1 also exhibited strong downregulation in PBL samples due to infection. One
of the targets that we observed, CD74, was consistently downregulated in the bacterial strains in
both sample sets. It is interesting that EseK does not heavily affect the downregulation of CD74
compared to the WT, even though it was shown to bind with CD74. It is likely that the effect of
EseK on CD74 is at the level of the protein and this will require further testing. CD74
downregulation in the presence of E. ictaluri could infer several roles in bacterial regulation of
the cell, because CD74 is involved in numerous functions in the cell, especially APCs (30).
Some well-documented functions include aiding assembly, as well as the timing of peptide
Treatment Tank Day 0 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day 10
Uninf. t34 59.3 23.4 27.0 57.3 47.9 57.9 69.0 63.7 67.2 83.6 28.5
Uninf. t37 44.2 14.8 32.6 48.2 58.2 58.8 63.9 58.3 49.9 78.3 33.6
Uninf. t40 31.2 16.4 23.1 49.2 34.3 41.5 64.4 58.9 47.2 68.4 32.6
WT t36 68.6 12.8 48.2 44.0 26.2 53.6 65.4 48.7 71.0 71.9 50.4
WT t42 40.1 15.5 32.6 38.3 66.3 53.5 62.2 49.4 46.2 73.0 41.0
WT t45 51.1 11.4 24.0 25.3 42.8 48.3 52.7 61.3 33.4 47.5 37.9
ΔeseK t35 85.4 21.4 25.0 54.5 53.9 62.1 69.2 68.4 60.4 52.2 27.9
ΔeseK t39 44.2 25.4 22.6 48.7 35.6 72.0 50.9 45.6 37.4 50.7 20.6
ΔeseK t44 24.3 18.7 16.7 57.9 34.7 57.5 66.4 81.2 28.9 77.7 55.1
0 1 2 3 4 5 6 7 8 9 10
0
20
40
60
80
100
CD3+ Lymphocytes
Day
Perc
en
t
Uninfected
ΔeseK
WT
94
binding to MHC class II, acting as a binding ligand for MIF, and cross-presentation to MHC
Class I (31). Any one of these functions could have a massive impact on the ability of APC’s to
mount a proper cell-mediated adaptive immune response, ranging from lack of MHC class II
assembly, MIF binding, or cross-presentation to MHC class I. Unfortunately, our present study
did not classify the regulation of MHC class II, so we can only speculate as to its regulation.
Beyond the major role in downregulation of T cell-mediated responses, CD74 is implied
in other roles through varying levels of experimentation in mammalian species: potentially
modifying the proteolytic activity of endosomes, thereby preserving epitopes for antigen
presentation (32); carrying out regulatory functions affecting B cells and dendritic cells in mice,
using the cytosolic of the protein (33, 34); utilizing that same domain to facilitate endosomal
fusions, thereby accelerating the speed at which antigens are trafficked through the endocytic
pathway (32, 35). Furthermore, CD74 may also be involved in the migration of dendritic cells
and B cells through an interaction with myosin II (4). CD74 was reported in soluble forms in
humans able to form complexes with circulating MIF (36). If any of these things are also able to
occur in catfish, it could explain some of the expression results we found.
In this study, MIF accumulation was observed in the bacterial strains compared to the
Sham in both sample sets, although it was not as robust in PBL samples. As stated, CD74 acts as
a binding ligand for MIF and could form complexes with MIF in circulation (PBL samples). As a
consequence, this interaction could be suppressing MIF’s ability to enhance the pro-
inflammatory effect of cytokines, such as TNF-α (37). Finally, CD40L is typically expressed on
CD4+ T cells in mammals, and is an indicator of T cell activation (8). Studies conducted in
salmon and zebrafish with CD40L suggest the conservation of CD40-CD40L roles in fish and
mammals (38). CD40L also allows for the upregulation of cytokines, such as IL-1β, IL-6, IL-8,
95
IL-12, TNF-α, and IL-10, as well as type I IFNs (8). CD40L interaction also drives subset
differentiation towards a Th1 phenotype (39, 40). A similar role in the catfish could suggest that
loss of CD40L after E. ictaluri infection could indicate loss in activation and subset
differentiation of CD4 T cells and a reduced antibody response (8).
Head Kidney. The three previously mentioned T cell markers CD3, CD4 and CD8α, as
well as IL-8_2, showed significant differences in regulation for several consecutive days or for
day 7 in HK samples in response to E. ictaluri. Several other cytokines, such as IFNγ, IL-1β and
TGF-β1, also showed a difference in regulation, but these were all isolated to one or two non-
consecutive days, with the exception of IL-1β, which spiked on day 2 and 3 in both strains.
As with mammals, CD3 is present on all fish T cells, and we observed a downregulation
of CD3 expression in HK tissue on day 7 (41). This indicated that E. ictaluri suppresses T cell
populations towards the later days of infection in the HK. Downregulation of CD4 and CD8α in
HK samples in the latter days of this experiment gives additional support to the response
observed with CD3, but also implies a suppression of Th subset and CTL responses. CD4 and
CD8 also behave similarly in teleosts as their mammalian counterparts (42-47). However, one
catfish study suggests that catfish may have CD4+ CTLs in addition to CD8 + CTLs (48), and if
this is the case then the downregulation we observed in CD4 could suggest an additional role in
expression of CTL populations. This knowledge may explain the differences in expression seen
in the two CD4 variants. A study looking at CD4 and CD8 in the HK found an upregulation in
these two genes, an observation in contrast to this study. Differences in experimental design,
such as the length of time fish were allowed to acclimate before infection may explain the
discrepancies (49).
96
While the responses in T cells and CMI pathways are most interesting, we also saw
upregulation in IL-8 midway in this experiment, which was also observed in other studies (49,
50). The structure of catfish IL-8 likely allows attraction and recruitment of neutrophils, as in
mammals (13, 51). This would suggest that neutrophils are recruited to the HK shortly after
infection.
Additional indicators for the type of response seen in HK may be elucidated using IFN-γ,
IL-1β, and TGF-β1, which also exhibited changes in expression on more than one day, although
TGF-β1 was highly significant in PBL samples. Previous reports indicate an upregulation in
IFN-γ in response to E. ictaluri, a result also seen in this experiment (49). IFN-γ aids in an
antiviral state and drives CD4 T cells towards a cell-mediated Th1 response (52, 53). IFN-γ in
teleosts also acts on monocytes and macrophages to increase the production of nitric oxide and
reactive oxygen intermediates (ROI), as well as phagocyte activity in several species. Studies
show IFN-γ is capable of inducing expression of more than 2 dozen genes, which include STAT1
and TLR3 in catfish, and MHC class II β chain and respiratory burst in trout (52-54). IL-1β was
also significantly upregulated in WT compared to Sham in HK, as seen in other studies (49, 55).
Studies of these cytokines showed an ability to increase the expression of bactericidal and
phagocytic effects of HK leukocytes (51, 56, 57).
Our data shows that the upregulation of IFN-γ and IL-1β is not continuous in infected HK
samples. This suggests that there is a tendency to lean towards CMI responses in response to
infection of an intracellular pathogen, as expected. It appears that E. ictaluri keeps these
responses in check, possibly due to reduced activation of T cell related pathways by APC’s.
Peripheral Blood Leukocytes. In the PBL samples, the robust changes in T cell markers
were not as apparent as in the HK, but CD74, CD40L, and MIF followed the same trends.
97
Additionally TGF-β1 was downregulated. Pointed differences in regulation were also observed
in several genes, particularly IL-10 and IL-17. No change in CD3 transcripts or cell number was
observed in PBL samples, suggesting that T cell abundance is not affected in PBL samples
during the first several days of infection. Our flow cytometry data did not detect any changes
between CD3ε among treatments in PBL samples. This is in general agreement with the
nCounter® data, but it is important to note that the CD3ε antibody used in the flow cytometry
assay did not show the same shift in positive CD3ε populations for most of the experimental
samples as observed in the preliminary optimization experiments, leading to questions of this
particular antibodies binding efficiency to catfish CD3ε. This observation in overall T cell
populations may be supported by a recent study that found that CTL populations do not appear to
proliferate in the presence of E. ictaluri infected HKDM (58).
Consistent downregulation of TGF-β1 occurred in PBL samples. This occurrence in the
center of the experiment overlaps with other cytokines, such as IL-10 and IL-17, and could be
indicative of an attempt to regulate T cell leaning. TGF-β1 reduces cytotoxic responses and
acute phase responses of TNF-α induction of IL-1Β, IL-6 and IL-8 in fish (59, 60). TGF-β1
provides an interesting paradigm because, on its own, it suppresses immune responses secreted
by regulatory T cells, but in combination with IL-6, it allows Th17 differentiation (15). Because
TGF-β1 is so heavily downregulated in PBL samples, and IFN-γ is not differentially regulated,
this indicates that E. ictaluri is suppressing most Th subsets including CMI and T regulatory
responses. However, IL-10 and IL-17 were upregulated on approximately day 2 and day 5. IL-10
functions similarly in fish as in mammalian counterparts by suppressing inflammatory responses
(15). IL-17 is important in several tissues of catfish infected with E. ictaluri, such as gill, skin,
and intestine (61). The results seen with IL-10 and IL-17 could indicate an attempt to produce a
98
Th17 or Th2 subset response, but the strong downregulation of TGF-β1 and CD40L gives
credence to the idea that all T cell responses are being suppressed and that these minor
upregulations are knocked down by E. ictaluri in an attempt to control T cell responses.
The data suggests an influence of E. ictaluri on catfish to control T cell and acute phase
responses. This influence is seen in the HK as a reduction in T cell related markers likely leading
to a decrease in T cell activation and response, and also in PBL samples by a reduction in TGF-
β1 and general stabilization in cytokines known to play a part in differentiation and productivity
of other T cell subsets. This is further evidenced by the suppression of CD74, vital to initiation of
immune responses on APC and the reduction of CD40L, a marker of T cell activation. Taken
together this suggests the ability of E. ictaluri to persist in naïve catfish by suppressing CMI
responses.
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105
CHAPTER 5. GENERAL CONCLUSIONS
The scope of this work focused on better characterizing the immune response generated
by channel catfish to wild-type Edwardsiella ictaluri (WT). This was done ex vivo in head-
kidney-derived-macrophages (HKDM) and in vivo in the head-kidney (HK) and peripheral blood
leukocyte (PBL) samples. Additionally, the scope of this work was to characterize one of the
Type III Secretion System (T3SS) effectors, EseK, as it relates to virulence using the same
parameters tested for the WT. The hypotheses of this work were first, that the WT is specifically
capable of persisting in HKDM, and subsequently the host, by limiting cell-mediated immune
(CMI) responses. Additionally, we speculated that EseK, which is relevant in HKDM
replication, may be pertinent for the evasion of CMI responses.
The first goal of this work was to determine if EseK could be of interest to pursue further
characterization. The studies in Chapter 2 focused on confirming EseK’s host-binding protein
and determining the potential for an attenuated EseK mutant (ΔeseK) to provide protection
against E. ictaluri infection. EseK was fused to a 3XFLAG sequence for specific detection in a
mix of other highly homologous E. ictaluri leucine-rich-repeat (LRR) T3SS effectors using
specific FLAG antibody. This tagged protein can restore the WT phenotype, so it was used to
carry out a co-immunoprecipitation (Co-IP) using the tagged EseK and a HKDM whole-cell
lysate. As a follow up to a yeast-2-hybrid assay performed outside the scope of this work, Co-IP
was coupled with mass-spectrometry analysis to confirm an interaction of EseK with CD74 in
HKDM. As previously mentioned, both strategies have very low rates of false positives, so the
two items together are strong proof of the interaction between EseK and CD74 in HKDMs. The
interaction of EseK with CD74 is of interest because CD74 is highly pleiotropic in other
106
organisms, especially in cell-mediated immune pathways, as its expression is strongest in antigen
presenting cells (APC)s (1).
After confirming that CD74 is the binding partner of EseK, and that this bond could be of
practical benefit, ΔeseK was used to infect fish to determine its virulence relative to the WT and
if immersion exposure could protect against subsequent WT challenge. Vaccination is a critical
strategy in fish health, and in catfish oral or immersion vaccination with live attenuated E.
ictaluri strains is the common strategy to protect against infection with E. ictaluri (2-4). The
results showed a high degree of similarity in virulence and subsequent protection between the
WT and ΔeseK at the highest dose. The ΔeseK strain showed a high level of protection to
subsequent WT exposures at all tested doses 4 weeks post-vaccination (PV) in both trials, and
later exposure at 8 weeks also showed protection, although one trial had a drastically reduced
survival rate, with the lowest dose only providing 28% protection. Reasons ΔeseK provides
protection in a short window but not consistently for a longer duration could have to do with the
strength of the adaptive immune responses generated, specifically T cell-dependent antibody
generation and CMI responses. However, the ΔeseK strain is promising, because it does provide
a short-term protective response, with some extended protection observed in several doses,
suggesting that EseK is involved in regulation of the cell-mediated pathway. A vaccine using an
EseK deletion would be improved by finding and adding the component(s) that are aiding E.
ictaluri’s evasion of CMI responses.
The studies carried out in chapters 3 and 4 aimed to better characterize non-activated
HKDM and naïve fish in response to E. ictaluri infection with the hypothesis that naïve fish do
not mount robust CMI responses to E. ictaluri infection. Contrary to expectations, results did not
give additional indications of EseK’s role in CMI relative to the WT. While the expression data
107
was exciting because it showed that E. ictaluri clearly has a role in downregulating CD74, it was
also highly surprising in that the binding partner, EseK, seemingly is not highly pertinent to this
response, at least not at the transcriptional level. Because ΔeseK did not exhibit significant
change compared to WT, the remainder of this discussion will focus on the WT relative to non-
infected control samples.
The RNA-sequencing (RNA-seq) data from chapter 3 led to several immediate
observations of E. ictaluri’s interaction with non-activated HKDMs. The ingenuity pathway
analysis (IPA) predicted 180 pathways with significant regulating differences between WT
infected and uninfected HKDM. Among those pathways, the regulation of TNFR1/2 pathways
(5), the P13K/AKT pathway (6), the NF-κB virus signaling pathway, and the peroxisome
proliferator receptor (PPAR) signaling pathway indicate an M1 polarization (7). This was further
supported by the regulation of several other pathways, such as the IL-1 signaling pathway, the
acute phase response pathway, and the iNOS signaling pathway (8). In addition, previous
discoveries in the lab showed the ability of E. ictaluri to survive and replicate in Edwardsiella-
containing vacuoles (ECV) within HKDMs (9). This, in addition to the regulation of several
pathways seen in this work, such as the NF-κB viral and P13K/AKT pathways, the Tec Kinase
pathway, and the death receptor pathway, indicate that E. ictaluri infection facilitates a strong
inclination towards HKDM autophagy. While it is possible that the host eventually overcomes
bacterial evasion of autophagy, it appears more likely that E. ictaluri is largely unhindered by the
autophagic environment of the HKDM, like many other bacterial pathogens (10).
After analyzing the data from chapter 4, we found that the most striking results from the
RNA-seq data is the indication of E. ictaluri regulation of the CD40 pathway in HKDMs. The
CD40 pathway is downregulated, which suggests a limited ability to fully mature and activate T
108
cells, in the presence of E. ictaluri (11, 12). In chapter 4, we determined the naïve catfish
response to E. ictaluri. Our study focused on responses generated in the HK, a hematopoietic
tissue, and PBL’s, a potential indicator of systemic responses. The data showed a strong
downregulation of CD74 and CD40L, and upregulation of MIF in both HK and PBL samples in
response to E. ictaluri infection. CD74 was downregulated from day two, which is likely
indicative of E. ictaluri throttling T cell activation and responses, which include the CMI
involved T cell sets, CD8+ CTLs and the CD4+ Th1 subset. The downregulation of CD40L was
also of interest because CD40L allows for the expression of cytokines such as IL-1β, IL-6, IL-8,
IL-12, TNF-α, and IL-10, as well as type I IFNs (12). Additionally, other notable observations in
HK tissues showed a trend of downregulation towards the end of the experiment in T cell
markers for CD4 and CD8, and an upregulation of IL-8. In addition, TGF-β1 was highly
downregulated in PBL samples, possibly suggesting a reduction in several T cell subsets,
including regulatory T cells. TGF-β1 provides an interesting paradigm because, on its own, it
suppresses immune responses secreted by regulatory T cells, but in combination with IL-6, it
allows Th17 differentiation (13). The potential for Th17 differentiation is interesting because this
T cell subtype is more involved with neutrophil recruitment and controlling extracellular
bacteria, and E. ictaluri does not do either of these things (14). TGF-β1 also reduces cytotoxic
responses (nitric oxide), and acute phase responses in fish (15, 16).
The observation that the CD40 pathway is downregulated in HKDMs, and CD40L is also
downregulated in vivo supports the theory that E. ictaluri seemingly evades T cell dependent
responses by inhibiting the CD40-CD40L pathway. This would aid E. ictaluri’s ability to persist
in the catfish. Further research will need to be conducted to both confirm and better understand
exactly how E. ictaluri is downregulating the CD40 pathway.
109
In conclusion, the binding partner of EseK was determined to be CD74, confirming a
previous yeast-two-hybrid assay (data unpublished). A protection assay showed that exposure to
the ΔeseK strain has a protective effect on subsequent exposure to WT. Next, RNA-seq carried
out on infected HKDM showed several pathways differentially regulated compared to uninfected
HKDM, leading to M1 polarization. Interestingly, the pathway analysis also indicated the E.
ictaluri downregulated pathways leading to programmed cell death and instead favors host cell
survival and replication. Finally, immune responses were determined in vivo, which found that
EseK has a minor effect on virulence, but WT drastically modulates immune responses, likely
aiding in persistence in the host. The strongest observation from the combined data suggests that
this is occurring by a downregulation of the critical T cell activating pathway, CD40-CD40L.
Figure 5.1 Macrophage and T cell activation with A) CD74 production allowing for MHC class
II (MHC II) to migrate with antigen to the cell surface to be recognized by T cells, in turn
allowing CD40-CD40L activation to occur, and B) in the absence of CD74, CD40 and CD40L.
Created with BioRender.com.
110
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112
APPENDIX I: ABBREVIATIONS COMMONLY USED IN THIS
DISSERTATION
ANOVA- Analysis of variance
APC- antigen presenting cell
BA- Blood Agar
BHI- Brain Heart Infusion
CCMM- channel catfish macrophage media
CCO- channel catfish ovary
CD- cluster of differentiation
CFU- colony forming units
CMI- cell-mediated immunity
Co-IP- Co-immunoprecipitation
DNA-deoxyribonucleic acid
ECV- Edwardsiella-containing vacuole
ESC- enteric septicemia of channel catfish
HK- Head Kidney
HKDM- Head-Kidney Derived Macrophage
IFN- interferon
IL- interleukin
JAK- janus kinase
LRR- Leucine rich repeat
MHC- major histocompatibility complex
MIF- migration inhibitory factor
113
MLSA- multi-locus sequence analysis
O/N- overnight
PBL- Peripheral blood leukocytes
PCR- polymerase chain reaction
PV- post-vaccination
qRT-PCR- quantitative reverse transcriptase PCR
RNA- Ribonucleic acid
SCV- Salmonella-containing vacuole
SPI- Salmonella Pathogenicity Island
STAT- signal transduces and activators of transcription
T3SS- Type III Secretion System
T4SS- Type IV Secretion System
T6SS- Type VI Secretion System
TGF- transformation growth factor
Th- T helper
TNF- Tumor necrosis factor
WT- wild type
114
APPENDIX II: CHAPTER 1 SUPPLEMENTAL MATERIAL
eseK Nucleic Acid Sequence
ATGCCACTTTATGTCGGCTCCGGGTATTTCCCCGCCACCATCAGTAATAACCGTATTC
AGCGCATCGTCAGTGCAAATATCACTCCGGATATGAGCGTTCGGGAGAATGTTCATG
AGTATTTCAACTCAACACATAAGTCTGAAGCCCTGACCTGTATCCAGGAAATTTGTC
ATCCCCCAGCCGGAACGACACGGGACGCTGTAGTGGGTAGATTTGGGCGACTCAGG
GGACTCGCCTATCCTGGATTCGCGGATAAGATCAAGTCTGGCGACAAGGACAATGG
AGATAACCGCCTCTGTATCCTGGATGAAAACGGACAGGAAATGTTATCAGTCATCCT
TGGTGATGACGAAAAATATACCGTCATCTATCCAAATGGCAGGGTAACGCATGACC
TCAGCCTGCCCGCATCACAAGGCGATGAGGGTCTCCTGGCATCATGTACTTTCGCCA
CCGCGGGCCCACAAACAGCGGATGAGTATGAGGCTGTTTGGTTAGCCTGGGAAAGG
GCTGCGCCGCCAGCAGAGGCAGAATGCCGAACCCAGACAGTGCAGAAGCTACGTCA
ATGCATGCAGAATGACACCCGGCTGGATGTCTCTCACACCCCACTAACCAGTCTGCC
GCCGCTGCCCACCGGACTGCAGAGTCTGGACATCTCTTACACTTCACTGACCAAGCT
GCCGCCGCTGCCCGACGGACTGCAGAGTCTGGACGTCTCTCACACCTCACTGACCAA
GCTACCGACGCTGCCCCACGGACTACAGAGTCTGAACGTCTCTCACACTTCACTGAT
AGGCTTACCGCTGCTGCCCCACGGACTGCAGAGTCTGGACGGCTCTCACACCTCACT
GACAGGCTTACCGCCGCTGCCCCAGAGACTGCAGAGTCTGGACGTCTCTCACACCTC
ACTGACAGGCCTACCGCCGCTGCTCCACGGACTGCAGAGTCTGGACGTCTCTCACAC
TTCACTGACCCAGCTGCCGACGCTGCCCCAAGGGTTGCAAAGTCTCAACATTTCTCA
CACTTCACTGACCGACCTGCAGACGCTGCCCTCCAAACTGCAGAGGTTGGATGCCTC
TCACACCTCACTGGCCAAACTGCAGACGCTGCCCTCCAAACTGCAGAAGTTGGATGT
CTCTCACACCTCACTGACCGAGCTACCGAAGATGCCATCCAGACTGGAAACTCTGAA
TGTCTCAGGCACCAAAATGACCAAACTATCGAGTTTGCCCTACGGTCTAAAGACACT
GAATGCCTCAAATACCCTACTGACAAGAATGCCAAGGCTGTACAACGAACTGCAAA
ATCTGGACCTCTCTAACACCACAATAGACTTCATAGGCCCATTTGAACTTCCGTATG
GACTGCAAACGCTGGATGTCTCAGGCACCCGACTGATCAGACTGCCACAACTGCCC
ACCGGACTGCAGTCGCTGAATATGTCTCACTTACCCTTAAAAGCCCTACCCCATATG
CCATCCGGACTGCAGACGCTGAATATGTCTCACATCCAAAAACTGATCAACATTACG
CATCTTCCCACCGAACTGCAGACGCTGAATGTCTCTCAGACCCCACTGCTCAACCTG
TCACAGCTCCCCACCGGACTGCAGTCGCTGAATATCTCTGACACCCCACTGTACAGA
CTGCCGTCGCTGCCCCCTGTACTGCAAATGCTGGATGTCTCTGGCACCAACCTGATC
AACCTGCCAGAAAGCCTAGCCAGGCTATCGCGGGATACAACTGTCCTCATGCAGAA
TAATCACATGCCAGATAGTACGATTCAGTTATTACGAAACAGGGTCAATGAACCCG
ACTATCAGGGACCCAGGATAGAGTTTGATAGGGGAGCCTCTTCAGGCGTTCAGGAA
ACCAATGCCTTGCACTTGCTGATGGCTAACTGGATGACAATAGAGGAAGCTTCAGAT
GATAGATGGAAAACCTTCTGGAGTGTAGACGATGCCCGCGCCTTCAGCATGTTTCTC
AATCAGTTGAAAGAGACGAAAAATAATAAGTCAGCCGATTTTCGCAAACAGATAGC
CACCTGGCTAACCCTGCTGGCTAATGATGATGAGCTAAGAGCCAAAACCTTTGCCAT
GGCGACAGAGTCAACCTCAAGCTGTGAGGACCGGGTCACGCTGGCGATGAACAGTA
115
TGAAGAGCGTGCAACTGCTCCATAATGCTGAAAAAGGGAAATTCGACAACGATATC
CCGGGGCTCGTGTCGGTAGGTCGTGAAATGTTCCGCCTGGAGAAGCTGGAGCTGATT
GCCCGCGAGAAGATAAAAACGCTACGCGATGAGGTCTATGGGGGCGATGAAGATAA
AGTCGATGAGATTGAGGTTTTTCTTGGCTATCAGAACCAATTGAAAAAATCACTTGA
ACTGACCGGGGCCACTGACGAAATGCGATATTTTGACGTATCCGACATTACCGAGTC
AGACCTTCAGGCTGCTGAAATTCAGGTGAAAACCGCCGAGGACAGCCAGTTCGGGG
AGTGGATACTGCAGTGGGAGCCGTTGCACAAAGTACTGATACGTAAAAATAAGGAC
GACTGGGATGCGCTCATTGACAAGAAAATAGAGGATTATGAGCGTGAATACCAAGA
ATTATATGACACAGAGTTGGAGCCGGCAGGTCTGGTCGGCGACATCGAGTCTGAGC
GAACTATCGGCGCAAGAGCGATGGCGAGCACAGAAAAGTTATTTCAGCAAGGCCTA
CGCCCGCTGGCAGAGAAGTTGCTGGGCAAGCATCTGGGAGCCCGATGGTTGCTAGA
TGCGTCCCCTGTATAG
EseK Amino Acid Sequence
MPLYVGSGYFPATISNNRIQRIVSANITPDMSVRENVHEYFNSTHKSEALTCIQEICHPPA
GTTRDAVVGRFGRLRGLAYPGFADKIKSGDKDNGDNRLCILDENGQEMLSVILGDDEK
YTVIYPNGRVTHDLSLPASQGDEGLLASCTFATAGPQTADEYEAVWLAWERAAPPAEA
ECRTQTVQKLRQCMQNDTRLDVSHTPLTSLPPLPTGLQSLDISYTSLTKLPPLPDGLQSL
DVSHTSLTKLPTLPHGLQSLNVSHTSLIGLPLLPHGLQSLDGSHTSLTGLPPLPQRLQSLD
VSHTSLTGLPPLLHGLQSLDVSHTSLTQLPTLPQGLQSLNISHTSLTDLQTLPSKLQRLDA
SHTSLAKLQTLPSKLQKLDVSHTSLTELPKMPSRLETLNVSGTKMTKLSSLPYGLKTLNA
SNTLLTRMPRLYNELQNLDLSNTTIDFIGPFELPYGLQTLDVSGTRLIRLPQLPTGLQSLN
MSHLPLKALPHMPSGLQTLNMSHIQKLINITHLPTELQTLNVSQTPLLNLSQLPTGLQSLN
ISDTPLYRLPSLPPVLQMLDVSGTNLINLPESLARLSRDTTVLMQNNHMPDSTIQLLRNR
VNEPDYQGPRIEFDRGASSGVQETNALHLLMANWMTIEEASDDRWKTFWSVDDARAF
SMFLNQLKETKNNKSADFRKQIATWLTLLANDDELRAKTFAMATESTSSCEDRVTLAM
NSMKSVQLLHNAEKGKFDNDIPGLVSVGREMFRLEKLELIAREKIKTLRDEVYGGDEDK
VDEIEVFLGYQNQLKKSLELTGATDEMRYFDVSDITESDLQAAEIQVKTAEDSQFGEWIL
QWEPLHKVLIRKNKDDWDALIDKKIEDYEREYQELYDTELEPAGLVGDIESERTIGARA
MASTEKLFQQGLRPLAEKLLGKHLGARWLLDASPV(Stop)
116
Figure II.1: ΔeseK creation. Primer (P) 190 and P 197 were used to amplify a sequence directly upstream of eseK and P191 and P192
amplified the 3’ tail of the eseK gene. Overlap PCR was implemented via reverse complemented sequences embedded into the P197
and P191 primers by amplifying the two fragments using P190 and P192. Yellow line indicates translation region. Figure generated
using SnapGene® software (from GSL Biotech; available at snapgene.com)
117
Figure II.2: ΔeseK ligation to pRE107 plasmid. A) digest pRE107and ΔeseK using SacI and
XbaI, and B) Ligation of pRE107and ΔeseK. Figure generated using SnapGene® software (from
GSL Biotech; available at snapgene.com)
118
Figure II.3: ΔeseK on pRE107 for E. ictaluri genome insertion. The pRE107 plasmid carries a cis-acting oriT that allows the plasmid
to be transferred to the E. ictaluri chromosome. As the sacB gene carried on the plasmid is translated, it accumulates a polymer
sucrose in the periplasmic space and prevents bacterial growth. Figure generated using SnapGene® software (from GSL Biotech;
available at snapgene.com)
119
Figure II.4. EseK::3XFLAG creation A) digest pBBR1-MCS4 and eseK::3XFLAG (previously
amplified using OL1-3XFLAG primer) using SacI and XbaI, and B) Ligation of pBBR1-MCS4
to EseK::3XFLAG. Figure generated using SnapGene® software (from GSL Biotech; available
at snapgene.com)
APPENDIX II: CHAPTER 4 SUPPLEMENTAL MATERIAL
Appendix II, Table 1: Probe Targets for nCounter®
Gene
Target Accession Position Target Sequence # Hit
Isoforms Hit by
Probe
β2M NM_00120
0072.1
243-342 AATGGCGAGGTGATTCCAAATGCAGAACAGACCGACC
TGGCCTTTGAGAAGGGATGGAAGTTTCATCTGACCAAG
AGCGTCTCCTTCACTCCCACCAGCA
1 NM_001200072.1
ACTβ XM_01745
4668.1 1338-
1437 CTCAGGATCTAAAAACTGGAACGGTGAAGGTGACGGC
AATGTTTTTTGGCAAATAAGCATCCCCGAAGTTCTACA
ATGCATCTGAGGACTCAAAGTACTT
1 XM_017454668.1
EEF1A XM_01745
4316.1
1454-
1553
GGCTGCTGGTGCTGGCAAGGTCACGAAGTCTGCACAG
AAGGCTGCCAAGACCAAGTGAATTCTCATTCCAGATGT
GTTAAAGGTGGTGGGGCATCCTCCC
1 XM_017454316.1
MIF NM_00120
0304.1
264-363 TCGGGAAGATCGGAGGCTCGCAGAATAAACAGTATTC
CAAACTGCTCATGGGTGTGCTTCATAAACACCTGGGCA
TTTCACCTGACAGGATCTACATTAA
1 NM_001200304.1
CD74 XM_01748
4954.1
589-688 ACCTCGGCGCTTCCTGCTTTCGTGTTGGAGTCTAAGTGT
AAGATTGAGGCTGGGCAGGTCAAACCAGGCTTCTTCG
AGCCACAGTGTGATGAGGAGGGCC
2 XM_017484954.1;
XM_017484955.1
CD3ε XM_01749
1706.1
215-314 ATGTGAGTATCTCGGGTACCACAGTCACACTGACCTGT
CCAGCTGATCCGGAGGACACCATACAATGGTTCAAAT
ATGCACAAACAGACCCACTCTCACT
4 XM_017491706.1;
XM_017491707.1;
XM_017491709.1;
XM_017491708.1
CD4 NM_00120
0226.1
1333-
1432
AGACAGATGATGAGGTATAGATGCCGTAAGGGGAGAG
TCTGCTGCTGTAAGAATCCCAAGCCCAAAGGTTTCTAC
AAGACCTGAATGAAGCCTCTTCTTG
2 NM_001200226.1;
XM_017474004.1
(table cont’d)
121
Appendix II, Table 1 continued
Gene
Target Accession Position Target Sequence # Hit
Isoforms Hit by
Probe
CD4_2 NM_00120
0227.1
616-715 GTTGTTGGTCCTTTGAACACACCAAGGGAAGTTAAGAC
TCATGAAGGGGGCAGTGCAGTGCTCCCGTGTTTTCTAC
CTACCAAGAGCCAACTGCCTATAA
1 NM_001200227.1
CD40L XM_01747
3417.1 455-554 AGCGCTCCCATCAAACACACCATTAGTCAAGTTCTTGT
CGGTGCTGCTGCTGCTGCTAATGATACAGACGTTTGGA
GGGTTTCTCTACCTGTTCCATGCA
1 XM_017473417.1
CD8α
NM_00120
0331.1
113-212 ACAAGAATTATCCATCGACAGTCTTTTGGCTTCGACTG
AAAGAAAACGGCCAGGGCTTTGAGTACATTGCGTCGT
ACAGCAAGACTAAGAAATCAGGCAA
1 NM_001200331.1
CD8α_
2
XM_01746
6933.1 605-704 GCATCATTAGCTTTACTGCTGATTATTGCCTGCCTCACA
TCTGCCATGTGCTTTATATACAGAGGTCGCTGCGTGAG
ACCAAAACTAAAGACGGATCGCC
1 XM_017466933.1
IFN-γ NM_00120
0302.1 420-519 ACTCAGGATGAAACGCTGAAGAATCACTTGCACGAAG
TGAAAGACCAAATGAACAAGCTGAAAGAACACTACTT
CTCCGGCAAACATGCAGACATCAAGA
2 NM_001200302.1;
XM_017493646.1
IL-10 XM_01745
0800.1
888-987 AGAATTTCAGAACGCCCATCGACACCATCGGAAGCTTA
TTTCAAGAGCTCAAGAGGGAGCTGGTCAAATGTAGGA
GTTACTTCACATGCCGGAAACCTTT
1 XM_017450800.1
IL-12α XM_01747
2329.1
303-402 TACTGGTCAACCTTTAAATCTTACCGTGATCCAGATCG
AATCCTGGAACAGTCAGTGCTCAGAAGCATAGAGAAC
CTCATGCAGGACTGCTTTTCTTCCA
1 XM_017472329.1
IL-17A XM_01747
5825.1 354-453 CCGATATACAGCACCATTCTGGTGCTCACGCAGGACTC
AACAAACAGGAAGTGCTTCAGTGTGAAGTTCCAGAGA
GTCACCGTTGGCTGCACGTGTGTGT
1 XM_017475825.1
(table cont’d)
122
Appendix II, Table 1 continued
Gene
Target Accession Position Target Sequence # Hit
Isoforms Hit by
Probe
IL-1β NM_00120
0220.1
678-777 AGAGACTGAAGTCCATCCAGGAGAATGATGGCATGGA
ACGCTTCCTTTTCTTCAGAAACGGCACTGGTGACTCCC
TTAACACCTTCGAGTCGGTCAAATA
2 NM_001200220.1;
NM_001200219.1
IL-6 XM_01745
5306.1 607-706 GGGCGATCAATTACATGAAGACTACGAAATTAATCCA
ACACATGGCGAAGGAACACGGGTGGCCCTCCAAACAC
GAGCAATGAATTTCCTGATGTTGTAT
1 XM_017455306.1
IL-8_1 XM_01747
2609.1
288-387 CTGCAAGAACACAGAGGTCATTGCTGGCTTGGTGAGTG
GAGAAAAGATTTGCCTGAATCCTCGGACTGCATGGGTT
AAGAAACTTATCCAGTTCATTGAG
1 XM_017472609.1
IL-8_2 NM_00120
0175.1 299-398 AAATTCCAAGGGAAGAAGGGGAAAGAAGCAGAAGGA
GATCAAACGGCAAAACTGAAGTTTACAGCTGGAGAAT
TCTACACATATATGATTGCTCAACCTT
3 NM_001200175.1;
XM_017451175.1;
XM_017451174.1
IL-8_3 XM_01747
2610.1 385-484 TCTTGTGGAGGAGGATGTGTGTTATGCAATCTTTCAGT
TTCACTGGAGGCAGAATGGCTTTAAAAGGACCCTAAG
CTCAGCTTCTTAACTGAGAACATCT
1 XM_017472610.1
TGF-
β1
XM_01749
3613.1
1107-
1206
GTTGGAAATGGATACACCAACCCTCCGGCTATTATGCA
AACTACTGTATCGGCTCCTGTTCGTTTGTCTGGAACAC
GGAAAATAAGTACTCACAGGTGAT
3 XM_017493613.1;
XM_017493612.1;
XM_017493614.1
TNF-α NM_00120
0172.1
361-460 CCCGCAGGTTTCGAGCGTATCTATGCAGTGGTTCGACA
ACGCAGACCAGTCCTTCTCTTCAGGCTTGAAACTGGAG
GACAACGAGATCAAGATTCTCCGC
1 NM_001200172.1
APPENDIX III: FAILED AND ONGOING EXPERIMENTS
IFA and PLA. Two experiments that could help further this work would be determining
where in the macrophage EseK interacts with CD74, via a PLA, and a ubiquitination assay.
While EseK and CD74 interact (both) yeast-2-hybrid and Co-IP assays are highly artificial;
therefore, it would be helpful to determine if this interaction is occurring in a more native
situation, such as in the HKDM. This could give insight into if this interaction actually occurs in
HKDM, and if so, if it is localized to certain locations on and/or in the cell, as well as the degree
and frequency that this interaction takes place.
An experiment utilizing EseK::3XFLAG with anti-FLAG antibody in conjunction with
goat anti-CD74 antibody has not yielded successful PLA results (or IFA). It is possible that full
optimization with these two antibodies has not yet occurred, or it is also possible that the 3X
FLAG system is not useful in this particular system even though it was used in other similar
experiments in Salmonella (seen in chapter 2). While Salmonella is closely related to E. ictaluri,
it is possible that the difference in species and cell targets used in other experiments are enough
to account for this inability to replicate similar experiments in this system. If that is the case, then
this could potentially be resolved by switching the tag or transfecting the HKDM cells with EseK
attached to an expression plasmid.
Ubiquitination Assay. EseK contains an E3 ubiquitin ligase motif and a translocation
sequence. The translocation sequence was previously shown to prevent secretion through the
T3SS when deleted, but it is also of interest to know if the E3 ubiquitin ligase sequence is
providing some function. The proteasome is found in two primary locations in the cell: the
cytosol and the nucleus and can degrade protein after the protein is ubiquitinated, which is the
124
role of an E3 ubiquitin ligase motif. If EseK’s E3 ubiquitin ligase motif is functional, EseK may
be interacting with CD74 to ubiquitinate it, thus targeting it for destruction or modifying it to
carry out some other function. This would effectively prevent the formation of MHC class II and
might also limit MHC class I activity from cross-presentation, or various other functions CD74 is
involved with, discussed previously in this work. An attempt to observe this interaction was
carried out twice in HKDM. It is possible that the ubiquitin motif is not functional in EseK, or
that this interaction is taking place at a very particular time during infection that is outside the
scope of the present experimental design.
TNP-KLH Assay. An ongoing experiment looking at T independent antibody production
should aid in the in vivo studies. This will help determine what the antibody response is to WT
relative to uninfected cells, as well as ΔeseK. The goal of this study is to collect blood samples
from infected fish at a two-week interval over 11 weeks. Fish were injected with the bacterial
strain of interest as well as TNP-KLH, a T cell-dependent hapten-carrier system that will aid in
the isolation of T cell-dependent antibody responses. The purpose of injection was to control the
efficiency of infection by by-passing the typical entry routes. This also allowed us to infect the
fish at a much lower dosage known to produce antibody responses, thus giving us a better
probability that a significant number of fish would survive to the conclusion of the study in each
treatment. After sample collection, an ELISA will be conducted using plates coated with anti-
TNP to determine antibody responses. Separate ELISA’s (or WB’s) will also be conducted to
verify ESC infection. Based on the present work, we would expect to see a reduction in T cell-
dependent antibody responses in the WT, and ΔeseK relative to 65ST, the T3SS mutant.
125
126
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VITA
Elizabeth Griggs was born in Baton Rouge, Louisiana in December, 1988. She lived with her
parents, Thomas and Cathie Griggs, and her older sister Catherine through her early years. She
attended St. Alphonsus School during elementary and middle school, followed by high school at
St. Joseph’s Academy. While in high school she developed an interest in volunteer service and
was honored with an award for service in her senior year. After graduation, Elizabeth left Baton
Rouge to attend Louisiana Tech University in the much smaller city of Ruston, Louisiana. She
was studying Environmental Science when she happened to enroll in a class in microbiology
decided that she had found her calling. After receiving her bachelor’s degree in Environmental
Science, and with Dr. Giorno-McConnell’s urging, she enrolled in a master’s program in
Microbiology, and two years later received her master’s degree. During her years at Louisiana
Tech, she discovered a deep appreciation for the outdoors, and ever since then has enjoyed
outdoor activities such as camping and obstacle course races. After graduation Elizabeth moved
back home to attend the school several generations of her family have matriculated through,
Louisiana State University.