Available via license: CC BY 4.0
Content may be subject to copyright.
Microorganisms 2022, 10, 1735. https://doi.org/10.3390/microorganisms10091735 www.mdpi.com/journal/microorganisms
Article
Effect of Iron Limitation, Elevated Temperature, and
Florfenicol on the Proteome and Vesiculation of the Fish Patho-
gen Aeromonas salmonicida
Tobias Kroniger 1, Mina Mehanny 2,3,4, Rabea Schlüter 5, Anke Trautwein-Schult 1, Bernd Köllner 6
and Dörte Becher 1,*
1 Institute of Microbiology, Department of Microbial Proteomics, Center for Functional Genomics of
Microbes, University of Greifswald, 17489 Greifswald, Germany
2 Helmholtz Institute for Pharmaceutical Research Saarland, 66123 Saarbrücken, Germany
3 Department of Pharmacy, Saarland University, 66123 Saarbrücken, Germany
4 Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University,
Cairo 11566, Egypt
5 Imaging Center of the Department of Biology, University of Greifswald, 17489 Greifswald, Germany
6 Institute of Immunology, Friedrich-Loeffler-Institute, Federal Research Institute for Animal Health,
17493 Greifswald-Insel Riems, Germany
* Correspondence: dbecher@uni-greifswald.de; Tel.: +49-3834-420-5903
Abstract: We analyzed the proteomic response of the Gram-negative fish pathogen A. salmonicida to
iron limitation, an elevated incubation temperature, and the antibiotic florfenicol. Proteins from dif-
ferent subcellular fractions (cytosol, inner membrane, outer membrane, extracellular and outer
membrane vesicles) were enriched and analyzed. We identified several iron-regulated proteins that
were not reported in the literature for A. salmonicida before. We could also show that hemolysin, an
oxidative-stress-resistance chaperone, a putative hemin receptor, an M36 peptidase, and an unchar-
acterized protein were significantly higher in abundance not only under iron limitation but also
with an elevated incubation temperature. This may indicate that these proteins involved in the in-
fection process of A. salmonicida are induced by both factors. The analysis of the outer membrane
vesicles (OMVs) with and without applied stresses revealed significant differences in the proteo-
mes. OMVs were smaller and contained more cytoplasmic proteins after antibiotic treatment. After
cultivation with low iron availability, several iron-regulated proteins were found in the OMVs, in-
dicating that A. salmonicida OMVs potentially have a function in iron acquisition, as reported for
other bacteria. The presence of iron-regulated transporters further indicates that OMVs obtained
from ‘stressed’ bacteria might be suitable vaccine candidates that induce a protective anti-virulence
immune response.
Keywords: Aeromonas salmonicida; iron limitation; temperature; antibiotic; florfenicol; outer mem-
brane vesicles; proteomics; subcellular fractionation
1. Introduction
The Gram-negative bacterium Aeromonas salmonicida is one of the major fish patho-
gens and the causative agent of furunculosis disease, resulting in high mortality and eco-
nomic losses within the salmonid aquaculture industry. Many virulence factors of A. salm-
onicida have been reported to contribute to its pathogenicity. This includes the S-layer (or
A-layer), which consists of the virulence array protein A (VapA) that is involved in the
adhesion to macrophages [1], iron and heme acquisition systems [2–5], hemolysin/aeroly-
sin [6], nucleases [6], lipases [6], proteases [6,7], chitinases [8], and other proteins involved
in adhesion [9,10]. Further, A. salmonicida possesses a functional type-three secretion sys-
tem (T3SS) [11–13] with several effector proteins [14–16]. Structural components of the
Citation: Kroniger, T.; Mehanny, M.;
Schlüter, R.; Trautwein-Schult, A.;
Köllner, B.; Becher, D. Effect of Iron
Limitation, Elevated Temperature,
and Florfenicol on the Proteome and
Vesiculation of the Fish Pathogen
Aeromonas salmonicida.
Microorganisms 2022, 10, 1735.
https://doi.org/10.3390/
microorganisms10091735
Academic Editor: Steve Charette
Received: 30 June 2022
Accepted: 24 August 2022
Published: 27 August 2022
Publisher’s Note: MDPI stays
neutral with regard to jurisdictional
claims in published maps and
institutional affiliations.
Copyright: © 2022 by the authors. Li-
censee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and con-
ditions of the Creative Commons At-
tribution (CC BY) license (https://cre-
ativecommons.org/licenses/by/4.0/).
Microorganisms 2022, 10, 1735 2 of 24
T3SS are mainly encoded on the large pAsa5 plasmid [17,18]. The T3SS can be lost by
insertion-dependent rearrangements on the pAsa5 plasmid [19], which can be triggered
by stressful growth conditions such as high cultivation temperatures [17,19,20].
In the beginning, measures to handle furunculosis in the aquaculture industry were
based on antibiotics treatment, e.g., florfenicol [21], but due to observed resistance phe-
nomena, efforts were made to develop vaccines. The vaccines that are currently used gen-
erally consist of inactivated A. salmonicida [22,23] or subunit vaccine approaches applied
via intraperitoneal or intramuscular injection [24,25]. However, these vaccinations are la-
bor-intensive, require a certain size of fish, and may sometimes induce unwanted severe
side effects [22,26].
Recently, vaccines have been tested using bacterial (outer) membrane vesicles
(OMVs) [27,28]. These 20–400 nm-sized bubble-shaped entities can enclose proteins,
DNA, RNA, peptidoglycan, lipopolysaccharides, and toxins [28–32]. It has been shown
that the proteome of OMVs is dynamic and can change with environmental conditions
and external stresses [33–36]. Bacterial OMVs are reportedly involved in various biologi-
cal processes, including nutrient acquisition, intracellular communication, defense, stress
response, biofilm formation, and virulence [27,37–39]. In terms of vaccine development,
OMVs are an interesting platform as they present their antigens in their native confor-
mation on the surface, cannot replicate, are highly immunogenic, are comparatively easy
to bioengineer, and have already been successfully applied against other diseases such as
bacterial meningitis [27,40–42]. It is known that A. salmonicida [43] and other bacteria in
the genus Aeromonas [39,43] produce OMVs. While the OMV proteome has been investi-
gated for other members in this genus [44], the protein composition of OMVs derived
from A. salmonicida has not been studied yet.
Here, we utilize a bacterial subcellular fractionation approach, where proteins of the
cytosol (Cyt), inner membrane (IM), outer membrane (OM), extracellular space (Extra),
and outer membrane vesicles (OMVs) are enriched and analyzed. As the most abundant
bacterial proteins are in the cytoplasm, this method of subcellular fractionation allows the
reduction of sample complexity and, therefore, the dynamic range of the proteins and
allows the identification of proteins with lower abundance [45,46]. Further, the determi-
nation of the experimental subcellular localization of proteins allows a deeper under-
standing of protein function and is crucial for potential future vaccine development efforts
as membrane (lipo)proteins are especially highly immunogenic [47–51].
In this study, we analyze the effect of three stressors that the bacterium may face in
the environment or the aquaculture industry on the proteome of A. salmonicida on a sub-
cellular level. With this approach, the resulting data of the extracellular, membrane, and
OMV proteomes will be of value for future rational vaccine designs as proteins in these
localizations are at the host–pathogen interface and are potentially suitable vaccine can-
didates.
2. Materials and Methods
2.1. Bacterial Strain, Cultivation, Stress Conditions, and Harvest
The Aeromonas salmonicida subsp. salmonicida strain JF2267 (first described in [52]) was
grown in quadruplicates in RPMI 1640 medium (Thermo Fisher Scientific) supplemented
with 50 µM FeCl3 and 100 µM citric acid in a 13 °C temperature water bath under shaking
at 160 rpm (‘Ctrl’). Samples referred to as ‘FeLim’ were not supplemented with FeCl3 and
citric acid. Samples referred to as ‘AB’ were supplemented with 0.5 µg/mL florfenicol
(MedChemTronica) during log-phase (OD600 ~ 0.3–0.4). Samples referred to as ‘Temp’
were grown at 19 °C. Growth curves for the stress conditions are visualized in Figure S1.
For the analysis, bacteria were harvested at an OD600 of 0.9–1 by centrifugation at 10,000×
g for 20 min at 4 °C. The bacterial pellet was used to isolate the cytosolic, inner membrane,
and outer membrane protein subcellular fractions. To remove the remaining bacteria, the
supernatant was filtered twice using 0.45 µm PES bottle-top filter membranes (VWR) and
Microorganisms 2022, 10, 1735 3 of 24
used to prepare the extracellular fraction. For the OMV isolation, due to a higher yield of
OMVs, bacteria were harvested by centrifugation at 10,000× g for 20 min at 4 °C after
reaching the stationary phase for at least 3 h. The OMV-containing supernatant was fil-
tered using a 0.45 µm bottle-top filter membrane to remove the remaining bacteria and
processed as described in ‘Preparation of OMV protein fraction’.
2.2. Preparation of Cytosolic, Inner Membrane, and Outer Membrane Protein Fractions
Bacterial cell pellets were resuspended in TE buffer (10 mM Tris-HCl, 1 mM EDTA,
pH 7.25), and bacteria were disrupted via sonication in 5 cycles at -0.55 W in 0.7 s intervals
for 1 min on ice. The total energy input was 0.7 kJ. Afterward, the cell extract was centri-
fuged for 10 min at 15,000× g and 4 °C to remove cell debris, and the supernatant was
transferred into a new reaction tube and ultracentrifuged at 100,000× g for 1 h at 4 °C to
pellet bacterial membranes. The supernatant contained the cytosolic proteins referred to
as ‘Cyt’. The pellet was washed with HEPES (10 mM, pH 7.4) to remove potential contam-
inants and ultracentrifuged again. Afterward, the pellet was resuspended in 1 % (w/v) n-
Lauroylsarcosine in 10 mM HEPES, which selectively solubilizes outer membrane pro-
teins, as described by [53], and incubated for 30 min at 37 °C under shaking and ultracen-
trifuged for 1 h at 100,000× g and 4 °C subsequently. The supernatant contained the pro-
teins of the inner membrane, referred to as ‘IM’. The pellet was washed in 10 mM HEPES
(pH 7.4) and ultracentrifuged for 1 h at 100,000× g at 4 °C. The pellet contained the proteins
of the outer membrane, referred to as ‘OM’. Prepared fractions were stored at -20 °C.
2.3. Preparation of OMV Protein Fraction
The filtered supernatant was concentrated ~20-fold using tangential flow filtration
(Ä kta flux, GE Healthcare) with a nominal molecular weight cut-off of 100 kDa (UFP-100-
C-3X2MA, Cytiva) to volumes that can be used in ultracentrifugation. Samples were ul-
tracentrifuged afterward at 100,000× g for 3 h at 4 °C. The pellet was washed in PBS to
remove potential contaminants and ultracentrifuged again for 3 h at 100,000× g and 4 °C.
The outer membrane vesicle containing the pellet was resuspended in PBS; the fraction is
referred to as ‘OMV’ and was stored at −20 °C.
2.4. OMV Nanoparticle-Tracking Analysis
The particle size distribution and yield of bacterial outer membrane vesicles were
measured using nanoparticle-tracking analysis (NTA, LM-10, Malvern, UK), as described
earlier [33]. Briefly, samples were diluted up to 1:1000 in filtered PBS to keep the particle
concentration within the recommended range for reproducibility of the NanoSight LM-10
microscope. Around 200 µL of diluted OMVs were introduced into a green laser-illumi-
nated chamber. Each sample was measured twice, in which three high-sensitivity 30 s
videos at a camera level of 13–15 were recorded, then processed with NanoSight 3.1 soft-
ware. Technical replicates were averaged.
2.5. S-Trap Protein Digestion and Peptide Fractionation
The S-Trap protein digest was performed according to the manufacturer’s protocol
(ProtiFi) with minor modifications. Protein concentrations were determined by BCA assay
according to the manufacturer’s instructions (Thermo Fisher Scientific). For the protein
digest, 20 µ g of protein of the Cyt, IM, OM, and OMV fractions was mixed 1:1 with 2×
lysis buffer (10% SDS, 100 mM TEAB, pH 7.55). Afterward, proteins were reduced in 20
mM DTT for 10 min at 95 °C and alkylated in 40 mM IAA for 30 min in the dark. Samples
were acidified by the addition of phosphoric acid to a final concentration of 1.2% and
diluted 1:7 with S-Trap binding buffer (90% methanol, 100 mM TEAB, pH 7.1). The pro-
teins were digested with 1:50 trypsin in 50 mM TEAB for 3 h at 47 °C in S-Trap microcol-
umns and the peptides were eluted from the columns using 50 mM TEAB, followed by
Microorganisms 2022, 10, 1735 4 of 24
0.1% aqueous acetic acid and 60% acetonitrile containing 0.1% acetic acid. The peptides
were dried using a vacuum centrifuge.
To reduce the sample complexity of the samples, basic reverse-phase peptide frac-
tionation was performed as described previously [29]. In short, peptides were loaded onto
in-house packed C18 micro spin columns (Dr. Maisch HPLC GmbH ReproSil pur C18,
pore size 300 Å , particle size 5.0 µm) and eluted in eight fractions with increasing acetoni-
trile concentrations ranging from 5% to 50% in a high-pH solution (0.1% triethylamine).
The eluates of fractions 1 and 5, 2 and 6, 3 and 7, and 4 and 8 were pooled. Peptides were
dried using a vacuum centrifuge, resuspended in 20 µ L buffer A (0.1% acetic acid), and
stored at −20 °C until LC–MS/MS measurement.
2.6. Preparation of the Extracellular Protein Fraction and In-Gel Digestion
Extracellular proteins were enriched using StrataClean affinity beads (Agilent), as
described before [54]. In brief, 20 µL of primed StrataClean beads were incubated with 10
mL of sterile-filtered bacterial culture supernatant in an overhead shaker overnight at 4
°C. The next day, the bead suspension with bound proteins was centrifuged for 45 min at
10,000× g and 4 °C. Afterward, the pellet was dried using a vacuum centrifuge, and the
proteins were separated from the beads by SDS-PAGE. The separation was performed
with 130 V until the solvent front traveled for roughly 3 cm. The gel was fixated and Coo-
massie-stained, and the lanes were cut in three pieces of equal size and tryptically di-
gested. The dried peptides were resuspended in 10 µ L Aq. dest. and desalinated using
C18 ZipTips according to the manufacturer’s protocol (Merck Millipore). Afterward, pep-
tides were resuspended in 20 µL buffer A (0.1% acetic acid) and stored at -20 °C until LC–
MS/MS measurement.
2.7. Bioinformatic Tools
2.7.1. PSORTb
PSORTb is a bioinformatic web-based online tool that predicts protein localizations
based on their amino acid sequence [55]. As input for the prediction, the UniProt proteome
of the A. salmonicida subsp. salmonicida strain M22710-11 (ID UP000232113, 4182 entries,
download 25th June 2021) was used as the stored UniProt proteome of the used A. salm-
onicida subsp. salmonicida strain JF2267 (ID UP000186585) was marked to be redundant to
the proteome of the M22710-11 strain at UniProt. The prediction was performed with
standard settings: Organism: Bacteria; Gram-stain: Gram-negative. The resulting PSORTb
prediction (version 3.0.2) differentiates between ‘unknown’, ‘cytoplasmic’, ‘cytoplasmic
membrane’, ‘periplasmic’, ‘outer membrane’, and ‘extracellular’ protein localization and
is available in Table S1.
2.7.2. SignalP
SignalP is a bioinformatic web-based online tool that predicts the presence of signal
peptides in proteins based on their amino acid sequence [56]. As input for the prediction,
the UniProt proteome of the A. salmonicida subsp. salmonicida strain M22710-11 was used.
The prediction was performed using the standard settings: Organism group: Gram-nega-
tive. The resulting SignalP prediction (version 5.0) differentiates between: ‘OTHER’: no
predicted signal peptide; ‘SP-Sec/SPI’: standard secretory signal peptides transported by
the Sec translocon and cleaved by signal peptidase I; ‘LIPO-Sec/SPII’: lipoprotein signal
peptides transported by the Sec translocon and cleaved by signal peptidase II; ‘TAT-
Tat/SPI’: Tat signal peptides transported by the Tat translocon and cleaved by signal pep-
tidase. The predictions for the A. salmonicida proteome are available in Table S1.
2.7.3. eggNOG
eggNOG is a bioinformatic web-based online tool that performs orthology-based
functional annotation of proteins based on the amino acid sequence of proteins [57]. As
Microorganisms 2022, 10, 1735 5 of 24
input for the prediction, the UniProt proteome of the A. salmonicida subsp. salmonicida
strain M22710-11 was used. The prediction was performed using the standard settings.
The resulting eggNOG prediction (version 5.0) of the proteome is available in Table S1.
2.8. Mass Spectrometry Data Acquisition and Analysis
Tryptic peptides of the subcellular fractions were separated on an Easy nLC 1200
liquid chromatography system (Thermo Fisher Scientific) with a reverse-phase C18 col-
umn (in-house packed, inner diameter 100 µm, outer diameter 360 µm, length 200 mm,
packed with Dr. Maisch ReproSil pur C18, pore size 120 Å , particle size 3.0 µ m) and a
column oven set to 45 °C. Peptides were loaded with 22 µL of buffer A (0.1% acetic acid)
at 400 bar and subsequently eluted with a non-linear 100 min gradient (OM, Extra, and
OMV fractions) or a non-linear 180 min gradient (Cyt and IM fraction) from 1% to 99%
buffer B (95% acetonitrile with 0.1% acetic acid) at a constant flow rate of 300 nl/min. Elut-
ing peptides were measured in an Orbitrap Elite mass spectrometer (Thermo Fisher Sci-
entific) in a data-dependent mode. The MS1 scan was recorded in the orbitrap with a mass
window of 300–1700 m/z and a resolution of 60,000. The 20 most intense precursor ions
(ions with an unassigned charge or a charge of 1 were excluded) were selected for CID
fragmentation with a collision energy of 35%. The resulting MS/MS spectra were meas-
ured by the linear ion trap.
The resulting *.raw-files were searched with MaxQuant software (version 2.0.1.0) [58]
against the UniProt proteome of the A. salmonicida subsp. salmonicida strain M22710-11 (ID
UP000232113, 4182 entries, download 25th June 2021). For detection of contaminations, the
cRAP contaminants list was used. The search was performed with a maximum of two
missed cleavages, oxidation (M) and acetylation (protein N-term) as variable modifica-
tions, and carbamidomethylation (C) as a fixed modification. Proteins were identified
with a minimum of two peptides per protein group, with at least one unique peptide.
Match between runs was enabled between biological replicates. For protein quantifica-
tion, unique and razor peptides were used, and the label-free quantification (LFQ) calcu-
lation was performed separately for each of the enriched subcellular fractions.
The resulting data were analyzed with Perseus software (version 1.6.15.0) [59]. Data
were filtered based on hits against the reverse database, identified by site and the contam-
ination list of MaxQuant. For statistical testing, only proteins with quantitative data in at
least 3 out of 4 replicates of a condition in one subcellular fraction were considered. To
also consider proteins that are on/off regulated, missing values were imputed from the
normal distribution, and two-sided Student’s t-tests with a false discovery rate of 0.05
were performed.
2.9. Transmission Electron Microscopy
Cells were fixed (1% glutaraldehyde, 4% paraformaldehyde, 0.2% picric acid, 50 mM
sodium azide in 20 mM HEPES buffer) for 30 min at room temperature and then stored at
4 °C until further processing. Subsequent to embedding in low gelling agarose, cells were
washed in washing buffer (20 mM cacodylate buffer pH 7, 10 mM calcium chloride) two
times for 10 min each time, postfixed in 2% osmium tetroxide in washing buffer for 1 h,
washed with deionized water for 5 min, washed with 0.05% sodium chloride two times
for 5 min, and then stained with 2% uranyl acetate in 0.05% sodium chloride for 30 min.
Cells were washed with deionized water three times for 5 min each time, and after dehy-
dration in a graded series of ethanol (20%, 30%, 50%, 70%, 90% for 10 min each, 96% two
times for 10 min, 100% ethanol three times for 10 min), the material was embedded in
epoxy resin (formerly EPON 812). Sections were cut on an ultramicrotome (Reichert Ul-
tracut, Leica UK Ltd., Milton Keynes, UK) and stained with 4% aqueous uranyl acetate for
3 min, followed by lead citrate for 30 s. After air drying, samples were analyzed with an
LEO 906 transmission electron microscope (Zeiss Microscopy Deutschland GmbH, Ober-
kochen, Germany) at an acceleration voltage of 80 kV. For image acquisition, a Sharpeye
wide-angle dual-speed CCD camera (Tröndle, Moorenweis, Germany) was used,
Microorganisms 2022, 10, 1735 6 of 24
operated by ImageSP software. Afterward, the micrographs were edited using Adobe
Photoshop CS6.
2.10. Field Emission Scanning Electron Microscopy
The cells were filtered onto a 0.2 µm polycarbonate filter (0.2 µm, GTTP, Merck
KGaA, Darmstadt), and cells adsorbed to this filter were fixed with a fixation solution (1%
glutaraldehyde, 4% paraformaldehyde, 0.2% picric acid in 5 mM HEPES buffer) for 1 h at
room temperature (RT) and then at 4 °C until further processing. Subsequently, samples
were treated with 2% tannic acid in washing buffer (100 mM cacodylate buffer (pH 7.0), 1
mM calcium chloride) for 1 h, 1% osmium tetroxide in washing buffer for 1 h, and 1%
thiocarbohydrazide for 30 min at RT, with washing steps in between. After treatment with
1% osmium tetroxide in washing buffer for 1 h at RT, the samples were washed three
times in washing buffer for 5 min each and then dehydrated in a graded series of aqueous
ethanol solutions (10%, 30%, 50%, 70% at 4 °C overnight, 90%) and in 100% ethanol on ice
for 15 min each step. Before the final change of 100% ethanol, samples were allowed to
reach room temperature and then critical-point-dried with liquid CO2. Finally, samples
were mounted on aluminum stubs, sputtered with an approximately 10-nm-thick
gold/palladium film, and examined with a Supra 40VP field emission scanning electron
microscope (Carl Zeiss Microscopy Deutschland GmbH, Oberkochen, Germany) using an
Everhart–Thornley SE detector and an in-lens detector at a 50:50 ratio at an acceleration
voltage of 5 kV. All micrographs were edited using Adobe Photoshop CS6.
3. Results
3.1. Evaluation of the Subcellular Fractionation
First, the success and purity of the subcellular fractionation protocol were evaluated
based on the protein abundances within the enriched subcellular fractions of the control
(Ctrl) condition. For this evaluation, two bioinformatics tools were used. The tool PSORTb
predicts the subcellular localization of a protein in silico based on the protein’s amino acid
sequence [55]. The tool SignalP, on the other hand, can predict the presence of signal pep-
tides of proteins in silico based on the amino acid sequence [56]. Protein quantities be-
longing to the same PSORTb-predicted protein localization (Figure 1A) or the same Sig-
nalP-predicted signal peptide (Figure 1B) were summed up and normalized by the total
LFQ intensity in the respective enriched subcellular fraction.
Figure 1. Overview of the predicted protein localizations and the presence of proteins with signal
peptides within the enriched subcellular fractions of the Ctrl condition. (A) Quantified proteins
Microorganisms 2022, 10, 1735 7 of 24
were grouped according to their PSORTb-predicted protein localization (U—unknown; C—cyto-
plasmic; CM—cytoplasmic membrane; P—periplasmic; OM—outer membrane; E—extracellular).
The protein abundances of these groups were normalized, and the distribution within the enriched
subcellular fractions of the Ctrl condition was plotted. The number of quantified proteins within the
enriched fractions is indicated above the bars. Error bars indicate standard deviations between rep-
licates (n = 4). (B) Quantified proteins were grouped according to their SignalP-predicted presence
of signal peptides (OTHER—no predicted signal peptide; SP—Sec translocon/signal peptidase I;
LIPO—Sec translocon/signal peptidase II; TAT—Tat translocon/signal peptidase I). The protein
abundances of these groups were normalized, and the distribution within the enriched subcellular
fractions of the Ctrl condition was plotted. The number of quantified proteins within the enriched
fractions is indicated above the bars. Error bars indicate standard deviations between replicates (n
= 4).
While the cytosolic proteins were by far the most abundant in the Cyt fraction, the
predicted cytosolic proteins were also highly abundant in the IM fraction, indicating an
imperfect fractionation. Nevertheless, inner membrane proteins were enriched in abun-
dance and number in the IM fraction compared to the other subcellular fractions. The OM
fraction was highly enriched with outer membrane proteins, and the Extra fraction was
comparatively enriched with extracellular proteins. In the Extra fraction, cytoplasmic pro-
teins and proteins of unknown localization were also highly abundant. In the OMV frac-
tion, proteins with unknown localization and predicted outer membrane proteins had the
highest combined abundance, but inner membrane proteins were also comparatively
abundant.
Next, similar to the PSORTb analysis, the presence and abundance of proteins with
signal peptides in the subcellular fractions of the Ctrl conditions were examined (Figure
1B). While proteins in the Cyt and IM fractions were mainly without a signal peptide,
proteins with a standard Sec/SPI secretion signal were enriched in the OM, Extra, and
OMV fractions. Additionally, proteins with a lipoprotein secretion signal were compara-
tively more abundant in the IM, OM, and OMV fractions. Similar visualizations of the
enriched proteins in the iron limitation (FeLim), elevated incubation temperature (Temp),
and antibiotic (AB) conditions are available in Figures S2 and S3. Lists of the total protein
identifications in the different conditions and the used bioinformatics tools (PSORTb, Sig-
nalP, eggNOG) are available in Table S1.
Microorganisms 2022, 10, 1735 8 of 24
3.2. Influence of the Stress Conditions on the Composition of the Subproteomes of A. salmonicida
Next, the proteomic response of the Aeromonas salmonicida strain JF2267 to the applied
stress conditions and their impact on the subproteomes are described. Most of the quan-
tified proteins were found in all of the applied conditions (Figure 2). Of all conditions, the
highest total number of proteins were quantified in the Cyt and IM fractions. Neverthe-
less, differences in the number of quantified proteins between the stress conditions were
observed. For example, the number of proteins in the OM fraction of the Temp condition
was nearly doubled compared to the other conditions. Additionally, more proteins were
quantified in the IM fraction of the FeLim condition compared to the other conditions.
Similarly, more proteins were quantified in the Extra and OMV fractions of the Ctrl and
AB conditions compared to the other conditions. Lists of the quantified proteins in each
subcellular fraction of the stress conditions are available in Table S2.
Figure 2. Overview of the overlap of quantified proteins between the stress conditions and the
control in the enriched subcellular fractions. Shown are the number of proteins that were quanti-
fied in at least 3 out of 4 replicates in each condition in the enriched subcellular fractions and their
respective overlap in quantified proteins with other conditions. Ctrl—control; FeLim—iron limita-
tion; AB—antibiotic stress; Temp—elevated temperature stress.
To pinpoint the function of proteins that had a changed abundance after the applica-
tion of the stress conditions, functional clusters of orthologous group (COG) annotation
were performed with eggNOG [57], and the differences in the quantitative protein distri-
bution between the conditions were analyzed afterward. We further analyzed significant
changes in protein abundances in response to the stress conditions for all enriched sub-
cellular fractions. For this analysis, only proteins with quantitative data in at least three
out of four replicates of a condition were considered. An overview of the number of pro-
teins with significantly changed abundance for each fraction and condition is shown in
Figure 3C and Figure 4C. Detailed tables of the significantly changed proteins, including
protein names, q-values, and the imputed LFQ values used for the statistics, are provided
in Table S3.
Microorganisms 2022, 10, 1735 9 of 24
Figure 3. Overview of the functional protein compositions in the enriched cytoplasmic and inner
membrane fractions. (A) Quantified proteins were grouped into functional categories that were
predicted by eggNOG (description of the one-letter code in (B)). The protein abundances of each bin
were normalized to the total protein abundances in the enriched fraction and condition. The distri-
bution within the conditions in the enriched cytosol (Cyt) and inner membrane (IM) fractions were
plotted. The number of quantified proteins within the conditions is indicated above the bars. Error
bars indicate standard deviations between replicates (n = 4). (B) COG one-letter code descriptions.
(C) The number of proteins with significantly changed abundance. Arrow pointing up: significantly
upregulated; Arrow pointing down: significantly downregulated. Detailed data are available in Ta-
ble S3.
In the Cyt fraction, proteins involved in ‘J-Translation, ribosomal structure, and bio-
genesis’ were the most abundant proteins in all conditions (Figure 3A). In the FeLim con-
dition, proteins of this functional category had a smaller share as many ribosomal proteins
were significantly less abundant (Figure 3C, Table S3). Contrary, proteins involved in ‘O—
Post-translational modification, protein turnover, and chaperones’, ‘E—Amino acid
transport and metabolism’, ‘P—Inorganic ion transport and metabolism’, and ‘Q—Sec-
ondary metabolites biosynthesis, transport, and catabolism’ were found to be relatively
more abundant in the Cyt and IM fractions of the FeLim condition than in the other con-
ditions. Many of these proteins were significantly changed in abundance (Table S3). These
proteins included several proteins involved in non-ribosomal peptide synthesis, iron
Microorganisms 2022, 10, 1735 10 of 24
transport and acquisition, hemolysin, aerolysin, and peptidases. Similar to the Cyt frac-
tion, proteins categorized as ‘J—Translation, ribosomal structure, and biogenesis’ were
highly abundant in all conditions of the IM fraction (Figure 3A). Proteins involved in ‘M—
Cell wall/membrane/envelope biogenesis’ were increased in the number of identifications
but were also in relative abundance in the IM fraction compared to the Cyt fraction. In the
Temp and AB conditions, few or no proteins were significantly changed in abundance
compared to the Ctrl condition (Figure 3C).
Figure 4. Overview of the functional protein compositions in the enriched outer membrane, ex-
tracellular, and outer membrane vesicle fractions. (A) Quantified proteins were grouped into func-
tional categories that were predicted by eggNOG (description of the one-letter code in (B)). The
protein abundances of each bin were normalized to the total protein abundances in the enriched
fraction and condition. The distributions within the conditions in the enriched outer membrane
(OM), extracellular (Extra), and outer membrane vesicle (OMV) fractions were plotted. The number
Microorganisms 2022, 10, 1735 11 of 24
of quantified proteins within the conditions is indicated above the bars. Error bars indicate standard
deviations between replicates (n = 4). (B) COG one-letter code descriptions. (C) The number of pro-
teins with significantly changed abundance. Arrow pointing up: significantly upregulated; Arrow
pointing down: significantly downregulated. Detailed data are available in Table S3.
In the OM fraction, proteins involved in ‘M—Cell wall/membrane/envelope biogen-
esis’ had the biggest relative abundance in all conditions (Figure 4A), followed by ‘J—
Translation, ribosomal structure, and biogenesis’ and ‘U—Intracellular trafficking, secre-
tion, and vesicular transport’. While the number of identified proteins was comparable to
the Ctrl condition, the relative abundance of proteins involved in ‘P—Inorganic ion
transport and metabolism’ was increased drastically in the FeLim condition. Proteins with
significantly increased abundance within this category (Figure 4C, Table S3) included sev-
eral TonB-dependent (siderophore) receptors. In the Temp condition, high deviations in
abundance and the number of identified proteins compared to other conditions were ob-
served, and 37 proteins were found to be significantly increased (Figure 4C, Table S3),
including hemolysin, peptidases, and TonB-dependent receptors. In the Extra fraction,
proteins without a COG annotation were the most abundant group, even though only 12–
19 proteins were quantified (Figure 4A). The most abundant protein in this fraction and
this category was the S-layer protein (Q6EVH0). Proteins categorized as ‘E—Amino acid
transport and metabolism’ were also abundant in the Extra fraction of all conditions. Ma-
jor differences were observed in the FeLim and AB conditions compared to the control. In
the FeLim condition, a relative increase in the abundance of proteins involved in ‘M—Cell
wall/membrane/envelope biogenesis’, ‘O—Post-translational modification, protein turn-
over, and chaperones’, ‘P—Inorganic ion transport and metabolism’, and ‘S—Function
unknown’ was observed. Significantly increased proteins in these categories included
porins, non-ribosomal peptide synthetases, isochromatases, and proteases (Table S3). In
contrast, proteins involved in all functions of ‘Information storage and processing’ were
decreased in abundance in the FeLim condition and increased in the AB condition. Pro-
teins involved in ‘F—Nucleotide transport and metabolism’ were also increased in rela-
tive abundance in the AB condition. In contrast, proteins involved in ‘C—Energy produc-
tion and conversion’ and without COG annotation were decreased in abundance in the
AB condition. In the OM fraction of the Temp condition, a type II secretion protein, he-
molysin, a DJ-1 family chaperone, alpha-amylase, pantothenate synthetase, and an un-
characterized protein were significantly increased in abundance (Figure 4C, Table S3). In
the OMV fraction, proteins involved in ‘M—Cell wall/membrane/envelope biogenesis’
and without COG annotation had the biggest share in abundance across all conditions
(Figure 4A). In the FeLim condition, a major increase in abundance was observed for pro-
teins involved in ‘P—Inorganic ion transport and metabolism’, while proteins categorized
as ‘S—Function unknown’ were decreased in abundance. Proteins with significantly in-
creased abundance in the FeLim OMVs included several TonB-dependent (iron) recep-
tors, peptidases, porins, and a lot of proteins without known function (Figure 4C, Table
S3). In the AB condition, proteins involved in ‘M—Cell wall/membrane/envelope biogen-
esis’ were found to be decreased in relative abundance, while proteins involved in ‘J—
Translation, ribosomal structure, and biogenesis’ and ‘S—Function unknown’ were in-
creased. Proteins involved in ‘H—Coenzyme transport and metabolism’ were found to be
increased in abundance in both the AB and Temp conditions. These changes were also
reflected in proteins with significantly changed abundances (Figure 4C, Table S3).
Overall, the condition with the highest number of proteins with significantly changed
abundance was the FeLim condition. Most protein abundances that were found to be in-
creased in the FeLim condition were non-ribosomal peptide synthetases, involved in si-
derophore biosynthesis/transport, other iron/heme transporters, TonB-dependent pro-
teins, chitin-degrading proteins, superoxide dismutases, stress response proteins, prote-
ases, peptidases, and many proteins with unknown function. Proteins with iron/heme or
iron–sulfur clusters as cofactors were the main group of proteins that were found to be
Microorganisms 2022, 10, 1735 12 of 24
less abundant in the FeLim condition. In response to the antibiotic, significant changes in
the proteome were mainly observed in the Extra and OMV fractions, where several cyto-
plasmic proteins, e.g., protein abundances involved in translation, ribosomal structure,
and biogenesis, were increased. Interestingly, one ABC transporter (A0A6N4D0R0) was
found to be significantly increased in abundance in the IM fraction and all replicates of
the OM fraction during the AB condition but was not quantified in any replicate in any
other condition in this study. In the Temp condition, no significant changes were detected
in the Cyt and IM fractions. Proteins that were observed to be more abundant in the Temp
condition were proteases, TonB-dependent proteins, transcriptional regulators, cell en-
velop proteins, a lysozyme inhibitor, chaperones, proteins with unknown function, and
proteins involved in virulence (Table S3).
3.3. The Outer Membrane Vesicles of A. salmonicida
To determine whether the iron limitation, elevated incubation temperature, and the
antibiotic conditions have an impact on the vesiculation of A. salmonicida besides the OMV
proteome itself, nanoparticle-tracking analysis (NTA) was performed, which allows the
determination of the concentration and size distribution of particles in the enriched frac-
tions.
While particle concentrations of the OMVs were comparable under Ctrl (Figure 5A),
FeLim, and AB conditions, fewer particles were observed in the Temp condition. Particles
enriched during the FeLim condition were slightly bigger on average (Figure 5B) but also
more diverse in their size distribution between replicates compared to the Ctrl condition
(Figure 5A). The particle size of OMVs enriched in the AB condition was drastically de-
creased and more heterogenous compared to the other conditions. OMVs enriched during
the Temp condition were slightly smaller but had a higher protein per particle ratio (Fig-
ure 5C). The differences in the size of the vesicles were visible in transmission electron
micrographs (TEMs) of the bacterium (Figure 6). Bacteria in all conditions had intact cell
membranes, and the blebbing of the OMVs was visible (indicated by arrows in Figure 6).
While the shedding of OMVs, in general, was also observed in scanning electron micro-
graphs (SEMs) (Figure S4), the size of the OMVs seemed to be more uniform in the TEMs
compared to the SEMs. In the SEMs, it was visible that the bacterial surface was fully
covered in OMVs. Further, nanotube-like structures that were connecting bacterial cells
were observed in all conditions (Figure S4).
Microorganisms 2022, 10, 1735 13 of 24
Figure 5. Nanoparticle-tracking analysis of Aeromonas salmonicida OMVs. (A) Size distribution
and concentration determination of the outer membrane vesicle fraction by nanoparticle-tracking
analysis (Ctrl—control; FeLim—iron limitation; Temp—elevated temperature; AB—antibiotic
stress). The colored areas indicate the 75% confidence intervals of the data between replicates, and
the red line indicates the mean particle size of the respective condition. (B) Mean particle sizes
within the outer membrane vesicle fraction of the applied conditions. (C) Protein-to-particle ratio
within the outer membrane vesicle fraction of the applied conditions. OMV protein concentration
determinations were obtained by BCA assay before S-Trap protein digest for mass spectrometry
analysis. Error bars indicate standard deviations between replicates.
Microorganisms 2022, 10, 1735 14 of 24
Figure 6. Transmission electron micrographs of Aeromonas salmonicida under control (Ctrl), iron
limitation (FeLim), elevated temperature (Temp), and antibiotic stress (AB) conditions. Arrows
indicate OMVs. Scale bars = 250 nm.
As already mentioned, the OMV proteome differed drastically between the applied
conditions (Figures 2 and 4C). For the analysis of such a high number of significantly
changed proteins, proteins were assigned to their functional COG category and the num-
ber of proteins significantly changed within this category was visualized (Figure 7).
Microorganisms 2022, 10, 1735 15 of 24
Figure 7. The number of significantly changed proteins for the OMVs derived in the stress con-
ditions. Significantly changed proteins were grouped according to their eggNOG-predicted func-
tional COG categories (FeLim—iron limitation; Temp—elevated temperature stress; AB—antibiotic
stress). On the right side are the descriptions of the COG one-letter code.
In all of the applied conditions, many proteins assigned to ‘M—Cell wall/mem-
brane/envelope biogenesis’, ‘T—Signal transduction mechanisms’, ‘U—Intracellular traf-
ficking, secretion, and vesicular transport’, ‘V—Defense mechanisms’, ‘C—Energy pro-
duction and conversion’, ‘P—Inorganic ion transport and metabolism’, and ‘S—Function
unknown’ were significantly less abundant compared to Ctrl OMVs (Figure 7). In the Fe-
Lim condition, numerous proteins categorized as ‘M—Cell wall/membrane/envelope bi-
ogenesis’, ‘U—Intracellular trafficking, secretion, and vesicular transport’, ‘P—Inorganic
ion transport and metabolism’, and ‘S—Function unknown’ or without COG annotation
were found to be increased in abundance (Figure 7). In contrast, various proteins with
functions in ‘J—Translation, ribosomal structure, and biogenesis’ and all other ‘Infor-
mation storage and processing’ categories, ‘F—Nucleotide transport and metabolism’,
‘G—Carbohydrate transport and metabolism’, and ‘H—Coenzyme transport and metab-
olism’ were significantly less abundant. Many proteins assigned to ‘J—Translation, ribo-
somal structure, and biogenesis’ and other ‘Information storage and processing’ catego-
ries were significantly more abundant in the AB condition. Further, several proteins in-
volved in metabolism, e.g., ‘E—Energy production and conversion’, ‘F—Nucleotide
transport and metabolism’, ‘G—Carbohydrate transport and metabolism’, and ‘H—Coen-
zyme transport and metabolism’, were more abundant in the OMVs of the AB condition
(Figure 7). In the Temp condition, mainly proteins involved in ‘E—Energy production and
conversion’ were upregulated.
4. Discussion
In this study, the proteomic adaption of A. salmonicida to three external stressors that
the bacterium may face in the environment or aquaculture was analyzed. For this, a sub-
cellular fractionation approach was applied, which allows a deeper protein coverage and
a more focused view on the significantly changed proteins within several localizations of
the bacterial cell. In the Ctrl condition, A. salmonicida was cultivated in an iron-supple-
mented RPMI medium at 13 °C, which is the optimal growth temperature of Atlantic
salmon, one of the hosts of A. salmonicida. The Ctrl condition served as a reference for the
success and number of identified proteins for the subcellular fractionations and compar-
ative proteomics with the stress conditions. In the first stress condition, bacteria were cul-
tivated as in the Ctrl condition but without iron supplementation, resulting in an iron
limitation stress that mimics an environment that the pathogen faces within the host. Iron
acquisition is one of the key tasks of bacterial pathogens as the availability of iron in the
host is scarce [60,61]. In the second stress condition, bacteria were cultivated at an elevated
temperature (Temp) of 19 °C. This condition mimics a behavioral fever where fish change
their thermal preference in response to an infection to amplify their innate immune re-
sponse [62,63]. In the third stress condition, bacteria were cultivated as in the control con-
dition, but 0.5 µg/mL of the antibiotic florfenicol was spiked in during the logarithmic
growth phase. The florfenicol concentration of 0.5 µg/mL was chosen as this concentration
has a measurable impact on the growth of A. salmonicida (Figure S5) while keeping the
cells viable (Figure 6). Florfenicol is a primarily bacteriostatic broad-spectrum antibiotic
that is licensed and used in aquaculture [64]. Additionally, all of these stressors have been
reported to influence the OMV proteome and the shedding of OMVs in general [35–
37,65,66]. The most important variations between the tested conditions are listed in Table
1.
Microorganisms 2022, 10, 1735 16 of 24
Table 1. Summary of the most important variations between the tested conditions.
Iron Limitation
Temperature
Antibiotics
Excerpt of the
proteomics results
Several upregulated IROMPs
(TonB-dependent proteins,
iron/siderophore transporters,
hemolysin, aerolysin)
Upregulated hemolysin,
putative hemin receptor,
oxidative-stress chaperon,
pullulanase, uncharacterized
protein
Increased ribosomal proteins in
extracellular space and outer
membrane vesicles
Vesiculation
(Mean particle size
of control: 172 nm)
Slightly increased vesicle size
(Mean particle size: 195 nm)
Slightly decreased vesicle size
(Mean particle size: 151 nm)
Decreased vesicle size (Mean
particle size: 102 nm) potentially
due to prophage induction
Vesiculation
amount
Comparable vesiculation
amount to control condition
Less vesiculation compared to
control
Comparable vesiculation
amount to control condition
4.1. Subcellular Fractionation
Overall, the applied protocol for subcellular protein enrichment was successful as
proteins were quantitatively and qualitatively enriched in their predicted protein locali-
zations compared to the quantitative data in the other enriched subcellular fractions (Fig-
ure 1A). This approach seemed to work best with cytosolic and outer membrane proteins,
as the Cyt and OM fractions yielded the highest purity of proteins predicted to be in these
localizations. The IM fractions yielded the highest numbers of identified proteins in all
conditions (Figure 2). As the share of cytosolic proteins in this fraction is very high (Figure
1A), many of the cytosolic proteins seem to be co-enriched. However, when compared to
the other enriched subcellular fractions, inner membrane proteins were enriched in the
IM fraction. In the Extra fraction, proteins with a secretion peptide were the most abun-
dant protein species. Nevertheless, proteins predicted to be cytosolic were also highly
abundant in this fraction. This may be explained by a certain amount of cell lysis but also
by proteins with a moonlighting function.
Bergh et al. analyzed putative moonlighting proteins that are present in A. salmonicida
and other bacteria [67]. They listed 35 putative moonlighting proteins and hypothesized
that these proteins may be secreted via OMVs. In fact, of the 35 putative moonlighting
proteins, we identified 34 in the Extra fraction and 32 in the OMV fraction. However, sev-
eral proteins were identified in the extracellular milieu of A. salmonicida that were not
identified in the OMVs and vice versa. Additionally, the relative abundances of numerous
proteins varied drastically between both subcellular fractions. In our data, 278 predicted
cytosolic proteins were identified in both the extracellular space and the OMVs (Table S2).
Of these, 197 were exclusively quantified in the extracellular fraction and 89 in the OMV
fraction. While some cytoplasmic-predicted proteins such as the malate dehydrogenase
(A0A6N4CWX9) or the 50S ribosomal protein L7/L12 (A0A6N4CQL8) were found highly
abundant in the Extra fraction, they were not found in the OMVs. Vice versa, for example,
the protein HflC (A0A6N4D0Q9), ATP-dependent Clp protease (A0A6N4CVB7), and
Beta-1,4-galactosyltransferase (A0A6N4CXK7) were found highly abundant in the OMV
fraction but not in the Extra fraction. The presence of cytoplasmic proteins within OMVs
can, in general, be explained by so-called outer–inner membrane vesicles (OIMVs), which
are double-bilayered MVs described for Gram-negative bacteria [68,69]. In our data, inner
membrane proteins were highly abundant in the OMV fraction (Figure 1A), giving
stronger evidence for the presence of OIMVs. OIMVs could also explain the differences in
size and the higher abundance of cytosolic proteins observed in the OMV fraction of the
AB condition (Figure S2), as other classes of antibiotics are reported to induce the bacterial
SOS response, which may lead to cell lysis and the production of OIMVs [68]. Overall, we
see a correlation between predicted cytoplasmic proteins in the extracellular and the OMV
proteomes, as hypothesized by Bergh et al.; however, several examples show that these
proteomes are quite different, and not all of these observations can be explained by the
Microorganisms 2022, 10, 1735 17 of 24
secretion of cytoplasmic proteins within OMVs. Our data demonstrate that the OMV pro-
teome varies greatly between the conditions. This may show one of the biological roles of
OMVs in bacteria, as they are reported to be involved in the fast modification of the bac-
terial cell surface proteome [70].
4.2. Response to the Iron Limitation
The acquisition of iron is essential for bacterial pathogens and often directly or indi-
rectly coupled to virulence [5]. This is one of the reasons why several studies have covered
the proteomic response of A. salmonicida to an environment with low iron availability in
the past decades [2–4,71–73]. Ebanks et al. identified three proteins that were upregulated
in response to low iron conditions [71]. These proteins were a 73 kD colicin receptor, a 76
kDa outer membrane heme receptor, and an 85 kDa ferric siderophore receptor. Our study
confirms these results, as homologs of all three proteins (Q6RBX7; Q6RBX6; Q6SLH5)
were found to be significantly upregulated. Najimi et al. described the siderophore bio-
synthesis cluster, which is essential for growth under iron limitation conditions [2]. We
found all six proteins belonging to the cluster (A0A6N4CWC2; A0A6N4CYM2;
A0A6N4CYP8; A0A6N4CW88; A0A6N4CZ10; A5I8G0) significantly increased in abun-
dance in response to the FeLim condition. Similarly, Najimia et al. described the heme
uptake genes of A. salmonicida [4]. Of the nine proteins described in this cluster, we found
seven proteins (Q6RBX6; A5I8G4; A0A6N4CZL3; A5I8G7; A5I8G8; A5I8G9; A5I8G3) to be
significantly increased in response to iron limitation. One protein (A5I8G5) was quantified
but not significantly changed, and one protein (A0A6N4D019) was not identified. In an-
other study, Najimi et al. performed a Fur titration assay and identified Fur-regulated
genes [3]. Our study found 5 of the 13 Fur-regulated proteins to be significantly changed
during iron limitation (A5I8G1; A0A6N4CYM8; Q6SLH5; A0A6N4CYM9;
A0A6N4CNL5), 5 were quantified but not significantly regulated (A5I8H2; A0A6N4CS56;
A0A6N4CUJ8; A5I8H6; A0A6N4CSB4), and 3 could not be identified (A0A6N4CSR5;
A5I8H4; A5I8H3).
In our work, we were able to report several additional proteins with significantly
increased abundance in a low iron environment (Table S3). Most of these proteins are in-
volved in (TonB-dependent) iron/siderophore transport and the biogenesis of these pro-
teins. Further, many proteins involved in cell wall synthesis, remodeling, and degradation
were significantly increased. Other proteins with significantly increased abundance are
involved in the virulence of the bacterium and may outline the quality of the presented
dataset. For example, A. salmonicida has two coded superoxide dismutases (SODs) (SodA-
Q7WYM8: SodB-Q7WYN0). While SodA was found to be significantly increased during
iron limitation and low abundant or missing in other conditions, SodB was identified in
the other conditions but low abundant or missing during iron limitation. The environ-
mental-dependent SOD expression is due to different cofactored prosthetic metals as
SodA is cofactored by manganese and SodB is cofactored by iron, as described previously
[74]. Similarly, most of the proteins that were significantly decreased in abundance in the
FeLim condition have iron, heme, or iron–sulfur clusters as cofactors. This also included,
for example, cytochrome c proteins, which were generally less abundant except for two
cytochrome c proteins that were induced during FeLim (A0A6N4CR45; A0A6N4CND1).
The environmental availability of iron has also been reported in other bacteria to influence
cytochrome c regulation [75]. Other proteins that may be involved in processes during
infection and were significantly increased in abundance during FeLim were chitin-bind-
ing and degrading proteins (A0A6N4CXW3; A0A6N4CWG8; A0A6N4D0S7), hemolysin
(A0A6N4CSV6), aerolysin (A0A6N4CNV5), flagellar/pili/fimbriae proteins
(A0A6N4CWZ1, A0A6N4CZ16, A0A6N4CVX1, A0A6N4CS92), lipase /acyltransferase
proteins (A0A6N4CSA9, A0A6N4CVH0), galactose binding proteins (A0A6N4CQ53),
and a glycosidase (A0A6N4CMG9). Interestingly, 49 of the proteins with significantly in-
creased abundance had no annotation or known function according to UniProt (Table S3).
Some of these were only detected during FeLim (A0A6N4D0E4; A0A6N4CZU3;
Microorganisms 2022, 10, 1735 18 of 24
A0A6N4CTR0; A0A6N4CPH4; A0A6N4CU70), giving strong evidence that these proteins
have functional or regulatory roles to cope with the FeLim condition and, therefore, po-
tentially during infection.
The OMVs formed during the iron limitation had similar size and concentration as
the OMVs derived during the control condition. Many iron-regulated (membrane) pro-
teins involved in the iron acquisition, considered promising antigens, were only found
during iron-limiting conditions on the OMVs. For example, of the 65 proteins Bergh et al.
identified in the supernatant that have antigenic homologs in other bacteria and constitute
candidates for a subunit vaccine [67], we identified 42 in the A. salmonicida OMVs during
FeLim. Of the 24 outer membrane-associated proteins that may be suitable as a subunit
vaccine candidate [67], we were able to identify 17 of them in the OMVs. Marana et al.
formulated three subunit vaccine candidates consisting of 14 proteins in total [24]. All
three subunit vaccines showed significantly lower mortalities compared to the control
groups. The OMVs derived during our study in the FeLim condition contained seven of
these proteins. Other conserved outer membrane proteins potentially suitable as vaccine
candidates include the outer membrane protein assembly factor BamA, the TonB-depend-
ent siderophore receptor, and the LPS assembly protein LptD [25]. All of them were iden-
tified in the OMV fraction during the FeLim condition. Therefore, OMVs of A. salmonicida
derived under iron-limiting conditions may represent a suitable platform for the develop-
ment of a new route of vaccination against furunculosis. Further, it has been shown that
OMVs conduct biological functions in other bacteria, including the acquisition of iron
[37,76]. The high number and quantity of iron transport proteins in A. salmonicida OMVs
could indicate a similar biological function of A. salmonicida OMVs in the acquisition of
iron.
4.3. Response to an Elevated Incubation Temperature
The speed and severity of the course of the furunculosis disease caused by A. salm-
onicida are associated with an increased water temperature [77]. While no proteins in the
Cyt and IM fractions were found to be significantly changed in their abundance, several
proteins were changed in the other subcellular fractions. This included proteins that play
a role during the infection. In the extracellular space, amongst others, a pullulanase
(A0A6N4CWY4), a hemolysin (A0A6N4CSV6), an oxidative-stress-resistance chaperone
(A0A6N4D0J0), an alpha-amylase (A0A6N4CPK2), and an uncharacterized protein
(A0A6N4CYU6) were significantly increased in abundance. An M36 peptidase
(A0A6N4CZ72) was also more abundant but slightly below the significance threshold. In
the outer membrane, a ligand-gated channel protein (putative hemin receptor) (A5I8G1)
was found to be significantly increased in abundance. The hemolysin, the oxidative-stress-
resistance chaperone, the ligand-gated channel protein (putative hemin receptor), the un-
characterized protein, and the M36 peptidase were significantly increased in the FeLim
condition, indicating that these proteins can be regulated by both iron limitation and ele-
vated temperature. That hemolysin can be regulated by temperature has already been
shown for other members of the Aeromonas genus [78]. This result shows that the rapid
disease progression experienced with a higher water temperature may be influenced by
infection-relevant proteins as some of them are regulated by both elevated temperature
and iron availability. This may be one way for the bacterium to bypass the behavioral
fever that fish can induce when facing an infection [62,63].
While, for many bacteria, an increased temperature is associated with increased pro-
duction of OMVs [38], we observed decreased OMV production with the elevated tem-
perature, which has been reported for other cold-water-adapted bacteria [79]. The applied
stress temperature of 19 °C is a temperature where the host experiences stress. A. salm-
onicida is not exclusively psychrophilic [80] but can also grow at higher temperatures.
Therefore, 19 °C may not be high enough to lead to a higher vesiculation phenotype, as
hypothesized. Whether this observation is caused by protein or lipid dynamics and
Microorganisms 2022, 10, 1735 19 of 24
whether higher vesiculation can be achieved with higher temperatures has to be clarified
in more detailed comparative studies.
4.4. Response to Florfenicol
Florfenicol is a broad-spectrum antibiotic that is mainly used in veterinary medicine
and aquaculture [64]. Even though florfenicol is considered a bacteriostatic, the data of
the Extra fraction suggests that bacterial cell lysis is occurring as the number of cytosolic
proteins and their abundances drastically increased compared to the control condition
(Figure S2; Table S2). Most of these proteins were ribosomal proteins and were involved
in translation, ribosomal structures, and biogenesis, which strengthens this hypothesis.
Similar to the Extra fraction, proteins involved in these functions were also the proteins
with the biggest increase in abundance in the OMV fraction. Together with the data of the
NTA analysis, this might propose that the OMVs were derived through a different mech-
anism of the bacterial parent cell as their protein cargo not only differed greatly from the
other conditions but the OMVs themselves were also drastically smaller (Figure 5). One
explanation for this observation could be that the binding to the 50S ribosomal subunit
and the resulting inhibition of protein synthesis by florfenicol result in a loss of regulation
of membrane maintenance and leakage of cytosolic proteins and the formation of smaller
OMVs with a different protein cargo. Similar to our results in other Gram-negative bacte-
ria, chloramphenicol, which has an analogous mode of action to florfenicol [81], did not
influence the amount of OMV production but significantly decreased OMV-associated
Shiga toxin 2a and OMV cytotoxicity compared to other classes of antibiotics [66]. In an-
other study, Devos et al. described the impact of antibiotics on the vesiculation of the
Gram-negative bacterium Stenotrophomonas maltophilia. They found that after antibiotic
treatment, a prophage was induced, which led to smaller and more heterogeneous MVs
that enclosed more cytoplasmic proteins [68]. As some phage proteins are abundant pro-
teins in the AB OMV fraction (Table S2), a similar effect may have been observed here for
A. salmonicida. Our results emphasize the drastic effects of florfenicol on the OMV shed-
ding and the OMV proteome. Both florfenicol [82] and OMVs [39] have been associated
with an increased biofilm formation of A. salmonicida. Therefore, it would be interesting
to see whether OMVs are involved in the observed effects of increased biofilm formation
after florfenicol treatment of A. salmonicida.
5. Conclusions
In this study, we analyzed the proteomic adaption of A. salmonicida to three environ-
mental stresses and were able to report quantitative data of roughly 2000 proteins in total
per condition. The presented data provide new insights into the subcellular adaption of
A. salmonicida, and we were able to expand the list of iron-regulated proteins of this im-
portant fish pathogen, which will be of value for future vaccine development efforts.
Many of the iron-regulated proteins were found in the OMV fraction of the bacterium that
was collected during iron-limiting conditions, indicating the potential of OMVs harvested
under iron-limiting conditions for future vaccine research as many of the iron-regulated
membrane proteins are considered promising antigens. After antibiotic treatment, the
OMV size was drastically decreased and resulted in a more heterogenous vesicle popula-
tion. We could also show that some proteins, including hemolysin, were not only signifi-
cantly increased in an environment with iron-limiting conditions but also by an elevated
incubation temperature. This highlights that some virulence factors of A. salmonicida are
not only regulated by iron availability but also by an elevated water temperature that fish
may prefer for the induction of behavioral fever.
Supplementary Materials: The following supporting information can be downloaded at:
https://www.mdpi.com/article/10.3390/microorganisms10091735/s1. Figure S1: Growth curves of
Aeromonas salmonicida grown under different stress conditions; Figure S2: Proteins quantified in the
applied conditions were clustered according to their PSORTb predicted protein localization (U—
Microorganisms 2022, 10, 1735 20 of 24
unknown; C—cytoplasmic; CM—cytoplasmic membrane; P—periplasmic; OM—outer membrane;
E—extracellular) for each of the enriched subcellular fractions. The protein abundancies of these
clusters were normalized and the distribution within the enriched subcellular fractions was plotted.
The number of quantified proteins in the experimental condition is indicated above the bars. Error
bars indicate standard deviations between replicates (n = 4); Figure S3: Quantified proteins were
clustered according to their SignalP predicted presence of signal pep-tides (OTHER—no predicted
signal peptide; SP - Sec/SPI: "standard" secretory signal peptides transported by the Sec translocon
and cleaved by signal peptidase I; LIPO - Sec/SPII: lipoprotein signal peptides transported by the
Sec translocon and cleaved by signal peptidase II; TAT - Tat/SPI: Tat signal peptides transported by
the Tat translocon and cleaved by signal peptidase). The protein abundancies of these clusters were
normalized and the distribution within the enriched subcellular fractions of the applied conditions
were plotted. of the applied conditions within the enriched subcellular fractions (A—Cytosol; B—
Inner membrane; C—Outer membrane; D—Extracellular; E—Outer membrane vesicle). The num-
ber of quantified proteins within the enriched fractions are indicated above the bars. Error bars in-
dicate standard deviations between replicates; Figure S4: Scanning electron micrographs of Aer-
omonas salmonicida under control (Ctrl), iron limitation (FeLim), elevated temperature (Temp) and
antibiotic stress (AB) conditions. Scale bars = 1 µm.; Figure S5: Effect of different florfenicol concen-
trations ranging from 0.25 µg/ml to 2 µg/ml on the growth of Aeromonas salmonicida JF2267; Table
S1: Effect of iron-limitation, elevated incubation temperature and florfenicol antibiotics on the sub-
cellular proteomes and the vesiculation of the fish pathogen Aeromonas salmonicida; Table S2: Effect
of iron-limitation, elevated incubation temperature and florfenicol antibiotics on the subcellular pro-
teomes and the vesiculation of the fish pathogen Aeromonas salmonicida; Table S3: Effect of iron-
limitation, elevated incubation temperature and florfenicol antibiotics on the subcellular proteomes
and the vesiculation of the fish pathogen Aeromonas salmonicida.
Author Contributions: Conceptualization, T.K. and D.B.; methodology, T.K. and D.B.; formal anal-
ysis, T.K.; investigation, T.K., M.M., and R.S.; resources, D.B. and B.K.; writing—original draft prep-
aration, T.K.; writing—review and editing, D.B., B.K., and A.T.-S.; visualization, T.K.; supervision,
D.B.; project administration, A.T.-S.; funding acquisition, D.B. and B.K. All authors have read and
agreed to the published version of the manuscript.
Funding: This research was funded by the European Maritime and Fisheries Fund and the federal
state Mecklenburg-Vorpommern (grant MV-II.1-LM-003/730217000003).
Institutional Review Board Statement: Not applicable
Informed Consent Statement: Not applicable
Data Availability Statement: The mass spectrometry proteomics data have been deposited with the
ProteomeXchange Consortium via the PRIDE partner repository [83] with the dataset identifier
PXD034641.
Acknowledgments: We thank Annette Meuche and Stefan Bock for excellent technical assistance
regarding electron microscopy.
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the
design of the study; in the collection, analyses, or interpretation of data; in the writing of the manu-
script; or in the decision to publish the results.
References
1. Garduno, R.A.; Moore, A.R.; Olivier, G.; Lizama, A.L.; Garduno, E.; Kay, W.W. Host Cell Invasion and Intracellular Residence
by Aeromonas salmonicida: Role of the S-Layer. Can. J. Microbiol. 2000, 46, 660–668. https://doi.org/10.1139/w00-034.
2. Najimi, M.; Lemos, M.L.; Osorio, C.R. Identification of Siderophore Biosynthesis Genes Essential for Growth of Aeromonas salm-
onicida under Iron Limitation Conditions. Appl. Environ. Microbiol. 2008, 74, 2341–2348. https://doi.org/10.1128/AEM.02728-07.
3. Najimi, M.; Lemos, M.L.; Osorio, C.R. Identification of Iron Regulated Genes in the Fish Pathogen Aeromonas salmonicida Subsp.
Salmonicida: Genetic Diversity and Evidence of Conserved Iron Uptake Systems. Vet. Microbiol. 2009, 133, 377–382.
https://doi.org/10.1016/j.vetmic.2008.07.008.
4. Najimi, M.; Lemos, M.L.; Osorio, C.R. Identification of Heme Uptake Genes in the Fish Pathogen Aeromonas salmonicida Subsp.
Salmonicida. Arch. Microbiol. 2008, 190, 439–449. https://doi.org/10.1007/s00203-008-0391-5.
5. Lemos, M.L.; Balado, M. Iron Uptake Mechanisms as Key Virulence Factors in Bacterial Fish Pathogens. J. Appl. Microbiol. 2020,
129, 104–115. https://doi.org/10.1111/jam.14595.
6. Chacón, M.R.; Figueras, M.J.; Castro-Escarpulli, G.; Soler, L.; Guarro, J. Distribution of Virulence Genes in Clinical and Envi-
ronmental Isolates of Aeromonas Spp. Antonie Van Leeuwenhoek 2003, 84, 269–278. https://doi.org/10.1023/A:1026042125243.
Microorganisms 2022, 10, 1735 21 of 24
7. Lee, K.K.; Ellis, A.E. Glycerophospholipid:Cholesterol Acyltransferase Complexed with Lipopolysaccharide (LPS) Is a Major
Lethal Exotoxin and Cytolysin of Aeromonas salmonicida: LPS Stabilizes and Enhances Toxicity of the Enzyme. J. Bacteriol. 1990,
172, 5382–5393. https://doi.org/10.1128/jb.172.9.5382-5393.1990.
8. Frederiksen, R.F.; Paspaliari, D.K.; Larsen, T.; Storgaard, B.G.; Larsen, M.H.; Ingmer, H.; Palcic, M.M.; Leisner, J.J. Bacterial
Chitinases and Chitin-Binding Proteins as Virulence Factors. Microbiology 2013, 159, 833–847.
https://doi.org/10.1099/mic.0.051839-0.
9. Dallaire-Dufresne, S.; Tanaka, K.H.; Trudel, M.V.; Lafaille, A.; Charette, S.J. Virulence, Genomic Features, and Plasticity of Aer-
omonas salmonicida Subsp. Salmonicida, the Causative Agent of Fish Furunculosis. Vet. Microbiol. 2014, 169, 1–7.
https://doi.org/10.1016/j.vetmic.2013.06.025.
10. Reith, M.E.; Singh, R.K.; Curtis, B.; Boyd, J.M.; Bouevitch, A.; Kimball, J.; Munholland, J.; Murphy, C.; Sarty, D.; Williams, J.; et
al. The Genome of Aeromonas salmonicida Subsp. Salmonicida A449: Insights into the Evolution of a Fish Pathogen. BMC Genom.
2008, 9, 1–15. https://doi.org/10.1186/1471-2164-9-427.
11. Burr, S.E.; Stuber, K.; Wahli, T.; Frey, J. Evidence for a Type III Secretion System in Aeromonas salmonicida Subsp. Salmonicida. J.
Bacteriol. 2002, 184, 5966–5970. https://doi.org/10.1128/JB.184.21.5966-5970.2002.
12. Burr, S.E.; Wahli, T.; Segner, H.; Pugovkin, D.; Frey, J. Association of Type III Secretion Genes with Virulence of Aeromonas
salmonicida Subsp. Salmonicida. Dis. Aquat. Organ. 2003, 57, 167–171. https://doi.org/10.3354/dao057167.
13. Vanden Bergh, P.; Frey, J. Aeromonas salmonicida Subsp. Salmonicida in the Light of Its Type-Three Secretion System. Microb.
Biotechnol. 2014, 7, 381–400. https://doi.org/10.1111/1751-7915.12091.
14. Origgi, F.C.; Benedicenti, O.; Segner, H.; Sattler, U.; Wahli, T.; Frey, J. Aeromonas salmonicida Type III Secretion System-Effectors-
Mediated Immune Suppression in Rainbow Trout (Oncorhynchus mykiss). Fish Shellfish Immunol. 2017, 60, 334–345.
https://doi.org/10.1016/j.fsi.2016.12.006.
15. Matys, J.; Turska-Szewczuk, A.; Sroka-Bartnicka, A. Role of Bacterial Secretion Systems and Effector Proteins -Insights into
Aeromonas Pathogenicity Mechanisms. Acta Biochim. Pol. 2020, 67, 283–293. https://doi.org/10.18388/abp.2020_5410.
16. Ebanks, R.O.; Knickle, L.C.; Goguen, M.; Boyd, J.M.; Pinto, D.M.; Reith, M.; Ross, N.W. Expression of and Secretion through the
Aeromonas salmonicida Type III Secretion System. Microbiology 2006, 152, 1275–1286. https://doi.org/10.1099/mic.0.28485-0.
17. Stuber, K.; Burr, S.E.; Braun, M.; Wahli, T.; Frey, J. Type III Secretion Genes in Aeromonas salmonicida Subsp. Salmonicida Are
Located on a Large Thermolabile Virulence Plasmid. J. Clin. Microbiol. 2003, 41, 3854–3856.
https://doi.org/10.1128/JCM.41.8.3854-3856.2003.
18. Vincent, A.T.; Hosseini, N.; Charette, S.J. The Aeromonas salmonicida Plasmidome: A Model of Modular Evolution and Genetic
Diversity. Ann. N. Y. Acad. Sci. 2021, 1488, 16–32. https://doi.org/10.1111/nyas.14503.
19. Tanaka, K.H.; Dallaire-Dufresne, S.; Daher, R.K.; Frenette, M.; Charette, S.J. An Insertion Sequence-Dependent Plasmid Rear-
rangement in Aeromonas salmonicida Causes the Loss of the Type Three Secretion System. PLoS ONE 2012, 7, e33725.
https://doi.org/10.1371/journal.pone.0033725.
20. Daher, R.K.; Filion, G.; Tan, S.G.E.; Dallaire-Dufresne, S.; Paquet, V.E.; Charette, S.J. Alteration of Virulence Factors and Rear-
rangement of PAsa5 Plasmid Caused by the Growth of Aeromonas salmonicida in Stressful Conditions. Vet. Microbiol. 2011, 152,
353–360. https://doi.org/10.1016/j.vetmic.2011.04.034.
21. Nordmo, R.; Holth Riseth, J.M.; Varma, K.J.; Sutherland, I.H.; Brokken, E.S. Evaluation of Florfenicol in Atlantic Salmon, Salmo
Salar L.: Efficacy against Furunculosis Due to Aeromonas salmonicida and Cold Water Vibriosis Due to Vibrio salmonicida. J. Fish
Dis. 1998, 21, 289–297. https://doi.org/10.1046/j.1365-2761.1998.00106.x.
22. Midtlyng, P.J.; Reitan, L.J.; Lillehaug, A.; Ramstad, A. Protection, Immune Responses and Side Effects in Atlantic Salmon (Salmo
salar L.) Vaccinated against Furunculosis by Different Procedures. Fish Shellfish Immunol. 1996, 6, 599–613.
https://doi.org/10.1006/fsim.1996.0055.
23. Marana, M.H.; Skov, J.; Chettri, J.K.; Krossøy, B.; Dalsgaard, I.; Kania, P.W.; Buchmann, K. Positive Correlation between Aer-
omonas salmonicida Vaccine Antigen Concentration and Protection in Vaccinated Rainbow Trout Oncorhynchus mykiss Evaluated
by a Tail Fin Infection Model. J. Fish Dis. 2017, 40, 507–516. https://doi.org/10.1111/jfd.12527.
24. Marana, M.H.; Von Gersdorff Jørgensen, L.; Skov, J.; Chettri, J.K.; Mattsson, A.H.; Dalsgaard, I.; Kania, P.W.; Buchmann, K.
Subunit Vaccine Candidates against Aeromonas salmonicida in Rainbow Trout Oncorhynchus mykiss. PLoS ONE 2017, 12, e0171944.
https://doi.org/10.1371/journal.pone.0171944.
25. Chukwu-Osazuwa, J.; Cao, T.; Vasquez, I.; Gnanagobal, H.; Hossain, A.; Machimbirike, V.I.; Santander, J. Comparative Reverse
Vaccinology of Piscirickettsia salmonis, Aeromonas salmonicida, Yersinia ruckeri, Vibrio anguillarum and Moritella viscosa, Frequent
Pathogens of Atlantic Salmon and Lumpfish Aquaculture. Vaccines 2022, 10, 473. https://doi.org/10.3390/vaccines10030473.
26. Midtlyng, P.J. A Field Study on Intraperitoneal Vaccination of Atlantic Salmon (Salmo salar L.) against Furunculosis. Fish Shellfish
Immunol. 1996, 6, 553–565. https://doi.org/10.1006/fsim.1996.0052.
27. Balhuizen, M.D.; Veldhuizen, E.J.A.; Haagsman, H.P. Outer Membrane Vesicle Induction and Isolation for Vaccine Develop-
ment. Front. Microbiol. 2021, 12, 79. https://doi.org/10.3389/fmicb.2021.629090.
28. Gilmore, W.J.; Johnston, E.L.; Zavan, L.; Bitto, N.J.; Kaparakis-Liaskos, M. Immunomodulatory Roles and Novel Applications
of Bacterial Membrane Vesicles. Mol. Immunol. 2021, 134, 72–85. https://doi.org/10.1016/j.molimm.2021.02.027.
29. Kroniger, T.; Flender, D.; Schlüter, R.; Köllner, B.; Trautwein-Schult, A.; Becher, D. Proteome Analysis of the Gram-Positive Fish
Pathogen Renibacterium salmoninarum Reveals Putative Role of Membrane Vesicles in Virulence. Sci. Rep. 2022, 12, 1–11.
https://doi.org/10.1038/s41598-022-06130-w.
Microorganisms 2022, 10, 1735 22 of 24
30. Toyofuku, M.; Nomura, N.; Eberl, L. Types and Origins of Bacterial Membrane Vesicles. Nat. Rev. Microbiol. 2019, 17, 13–24.
https://doi.org/10.1038/s41579-018-0112-2.
31. Schwechheimer, C.; Kuehn, M.J. Outer-Membrane Vesicles from Gram-Negative Bacteria: Biogenesis and Functions. Nat. Rev.
Microbiol. 2015, 13, 605–619. https://doi.org/10.1038/nrmicro3525.
32. Bitto, N.J.; Cheng, L.; Johnston, E.L.; Pathirana, R.; Phan, T.K.; Poon, I.K.H.; O’Brien-Simpson, N.M.; Hill, A.F.; Stinear, T.P.;
Kaparakis-Liaskos, M. Staphylococcus aureus Membrane Vesicles Contain Immunostimulatory DNA, RNA and Peptidoglycan
That Activate Innate Immune Receptors and Induce Autophagy. J. Extracell. Vesicles 2021, 10, e12080.
https://doi.org/10.1002/jev2.12080.
33. Mehanny, M.; Kroniger, T.; Koch, M.; Hoppstädter, J.; Becher, D.; Kiemer, A.K.; Lehr, C.M.; Fuhrmann, G. Yields and Immuno-
modulatory Effects of Pneumococcal Membrane Vesicles Differ with the Bacterial Growth Phase. Adv. Healthc. Mater. 2022, 11,
2101151. https://doi.org/10.1002/adhm.202101151.
34. Orench-Rivera, N.; Kuehn, M.J. Differential Packaging Into Outer Membrane Vesicles Upon Oxidative Stress Reveals a General
Mechanism for Cargo Selectivity. Front. Microbiol. 2021, 12, 1810. https://doi.org/10.3389/fmicb.2021.561863.
35. Keenan, J.I.; Allardyce, R.A. Iron Influences the Expression of Helicobacter Pylori Outer Membrane Vesicle-Associated Virulence
Factors. Eur. J. Gastroenterol. Hepatol. 2000, 12, 1267–1273. https://doi.org/10.1097/00042737-200012120-00002.
36. Briaud, P.; Frey, A.; Marino, E.C.; Bastock, R.A.; Zielinski, R.E.; Wiemels, R.E.; Keogh, R.A.; Murphy, E.R.; Shaw, L.N.; Carroll,
R.K. Temperature Influences the Composition and Cytotoxicity of Extracellular Vesicles in Staphylococcus aureus. mSphere 2021,
6, e00676–21. https://doi.org/10.1128/msphere.00676-21.
37. Prados-Rosales, R.; Weinrick, B.C.; Piqué, D.G.; Jacobs, W.R.; Casadevall, A.; Rodriguez, G.M. Role for Mycobacterium tubercu-
losis Membrane Vesicles in Iron Acquisition. J. Bacteriol. 2014, 196, 1250–1256. https://doi.org/10.1128/JB.01090-13.
38. McBroom, A.J.; Kuehn, M.J. Release of Outer Membrane Vesicles by Gram-Negative Bacteria Is a Novel Envelope Stress Re-
sponse. Mol. Microbiol. 2007, 63, 545–558. https://doi.org/10.1111/j.1365-2958.2006.05522.x.
39. Seike, S.; Kobayashi, H.; Ueda, M.; Takahashi, E.; Okamoto, K.; Yamanaka, H. Outer Membrane Vesicles Released From Aer-
omonas Strains Are Involved in the Biofilm Formation. Front. Microbiol. 2021, 11, 3374. https://doi.org/10.3389/fmicb.2020.613650.
40. Micoli, F.; MacLennan, C.A. Outer Membrane Vesicle Vaccines. Semin. Immunol. 2020, 50, 101433.
https://doi.org/10.1016/j.smim.2020.101433.
41. Narciso, A.R.; Iovino, F.; Thorsdottir, S.; Mellroth, P.; Codemo, M.; Spoerry, C.; Righetti, F.; Muschiol, S.; Normark, S.; Nan-
napaneni, P.; et al. Membrane Particles Evoke a Serotype-Independent Cross-Protection against Pneumococcal Infection That
Is Dependent on the Conserved Lipoproteins MalX and PrsA. Proc. Natl. Acad. Sci. USA 2022, 119, e2122386119.
https://doi.org/10.1073/pnas.2122386119.
42. Mehanny, M.; Lehr, C.M.; Fuhrmann, G. Extracellular Vesicles as Antigen Carriers for Novel Vaccination Avenues. Adv. Drug
Deliv. Rev. 2021, 173, 164–180. https://doi.org/10.1016/j.addr.2021.03.016.
43. Lusta, K.A.; Kozlovskii, Y.E. Outer Membrane Nanovesicles of Gram-Negative Bacteria Aeromonas hydrophila and Aeromonas
salmonicida. Microbiology 2011, 80, 519–524. https://doi.org/10.1134/S0026261711040138.
44. Avila-Calderón, E.D.; Otero-Olarra, J.E.; Flores-Romo, L.; Peralta, H.; Aguilera-Arreola, M.G.; Morales-García, M.R.; Calderón-
Amador, J.; Medina-Chávez, O.; Donis-Maturano, L.; Del Socorro Ruiz-Palma, M.; et al. The Outer Membrane Vesicles of Aer-
omonas hydrophila ATCC 7966: A Proteomic Analysis and Effect on Host Cells. Front. Microbiol. 2018, 9, 2765.
https://doi.org/10.3389/fmicb.2018.02765.
45. Thein, M.; Sauer, G.; Paramasivam, N.; Grin, I.; Linke, D. Efficient Subfractionation of Gram-Negative Bacteria for Proteomics
Studies. J. Proteome Res. 2010, 9, 6135–6147. https://doi.org/10.1021/pr1002438.
46. Malherbe, G.; Humphreys, D.P.; Davé, E. A Robust Fractionation Method for Protein Subcellular Localization Studies in Esche-
richia coli. Biotechniques 2019, 66, 171–178. https://doi.org/10.2144/btn-2018-0135.
47. Voß, F.; Kohler, T.P.; Meyer, T.; Abdullah, M.R.; Van Opzeeland, F.J.; Saleh, M.; Michalik, S.; Van Selm, S.; Schmidt, F.; De Jonge,
M.I.; et al. Intranasal Vaccination with Lipoproteins Confers Protection against Pneumococcal Colonisation. Front. Immunol.
2018, 9, 2405. https://doi.org/10.3389/fimmu.2018.02405.
48. Kim, Y.S.; Yoon, N.; Karisa, N.; Seo, S.; Lee, J.; Yoo, S.; Yoon, I.; Kim, Y.; Lee, H.; Ahn, J. Identification of Novel Immunogenic
Proteins against Streptococcus Parauberis in a Zebrafish Model by Reverse Vaccinology. Microb. Pathog. 2019, 127, 56–59.
https://doi.org/10.1016/j.micpath.2018.11.053.
49. Wilson, M.M.; Bernstein, H.D. Surface-Exposed Lipoproteins: An Emerging Secretion Phenomenon in Gram-Negative Bacteria.
Trends Microbiol. 2016, 24, 198–208. https://doi.org/10.1016/j.tim.2015.11.006.
50. Brandt, M.E.; Riley, B.S.; Radolf, J.D.; Norgard, M.V. Immunogenic Integral Membrane Proteins of Borrelia burgdorferi Are Lip-
oproteins. Infect. Immun. 1990, 58, 983–991. https://doi.org/10.1128/iai.58.4.983-991.1990.
51. Kovacs-Simon, A.; Titball, R.W.; Michell, S.L. Lipoproteins of Bacterial Pathogens. Infect. Immun. 2011, 79, 548–561.
https://doi.org/10.1128/IAI.00682-10.
52. Braun, M.; Stuber, K.; Schlatter, Y.; Wahli, T.; Kuhnert, P.; Frey, J. Characterization of an ADP-Ribosyltransferase Toxin (AexT)
from Aeromonas salmonicida Subsp. Salmonicida. J. Bacteriol. 2002, 184, 1851–1858. https://doi.org/10.1128/JB.184.7.1851-1858.2002.
53. Hobb, R.I.; Fields, J.A.; Burns, C.M.; Thompson, S.A. Evaluation of Procedures for Outer Membrane Isolation from Campylobacter
jejuni. Microbiology 2009, 155, 979–988. https://doi.org/10.1099/mic.0.024539-0.
Microorganisms 2022, 10, 1735 23 of 24
54. Bonn, F.; Bartel, J.; Büttner, K.; Hecker, M.; Otto, A.; Becher, D. Picking Vanished Proteins from the Void: How to Collect and
Ship/Share Extremely Dilute Proteins in a Reproducible and Highly Efficient Manner. Anal. Chem. 2014, 86, 7421–7427.
https://doi.org/10.1021/ac501189j.
55. Yu, N.Y.; Wagner, J.R.; Laird, M.R.; Melli, G.; Rey, S.; Lo, R.; Dao, P.; Cenk Sahinalp, S.; Ester, M.; Foster, L.J.; et al. PSORTb 3.0:
Improved Protein Subcellular Localization Prediction with Refined Localization Subcategories and Predictive Capabilities for
All Prokaryotes. Bioinformatics 2010, 26, 1608–1615. https://doi.org/10.1093/bioinformatics/btq249.
56. Almagro Armenteros, J.J.; Tsirigos, K.D.; Sønderby, C.K.; Petersen, T.N.; Winther, O.; Brunak, S.; von Heijne, G.; Nielsen, H.
SignalP 5.0 Improves Signal Peptide Predictions Using Deep Neural Networks. Nat. Biotechnol. 2019, 37, 420–423.
https://doi.org/10.1038/s41587-019-0036-z.
57. Huerta-Cepas, J.; Szklarczyk, D.; Heller, D.; Hernández-Plaza, A.; Forslund, S.K.; Cook, H.; Mende, D.R.; Letunic, I.; Rattei, T.;
Jensen, L.J.; et al. EggNOG 5.0: A Hierarchical, Functionally and Phylogenetically Annotated Orthology Resource Based on 5090
Organisms and 2502 Viruses. Nucleic Acids Res. 2019, 47, D309–D314. https://doi.org/10.1093/NAR/GKY1085.
58. Tyanova, S.; Temu, T.; Cox, J. The MaxQuant Computational Platform for Mass Spectrometry-Based Shotgun Proteomics. Nat.
Protoc. 2016, 11, 2301–2319. https://doi.org/10.1038/nprot.2016.136.
59. Tyanova, S.; Temu, T.; Sinitcyn, P.; Carlson, A.; Hein, M.Y.; Geiger, T.; Mann, M.; Cox, J. The Perseus Computational Platform
for Comprehensive Analysis of (Prote) Omics Data. Nat. Methods 2016, 13, 731–740. https://doi.org/10.1038/nmeth.3901.
60. Nairz, M.; Schroll, A.; Sonnweber, T.; Weiss, G. The Struggle for Iron—A Metal at the Host-Pathogen Interface. Cell. Microbiol.
2010, 12, 1691–1702. https://doi.org/10.1111/j.1462-5822.2010.01529.x.
61. Doherty, C.P. Host-Pathogen Interactions: The Role of Iron. J. Nutr. 2007, 137, 1341–1344. https://doi.org/10.1093/jn/137.5.1341.
62. Boltaña, S.; Rey, S.; Roher, N.; Vargas, R.; Huerta, M.; Huntingford, F.A.; Goetz, F.W.; Moore, J.; Garcia-Valtanen, P.; Estepa, A.;
et al. Behavioural Fever Is a Synergic Signal Amplifying the Innate Immune Response. Proc. R. Soc. B Biol. Sci. 2013, 280,
20131381. https://doi.org/10.1098/RSPB.2013.1381.
63. Huntingford, F.; Rey, S.; Quaggiotto, M.M. Behavioural Fever, Fish Welfare and What Farmers and Fishers Know. Appl. Anim.
Behav. Sci. 2020, 231, 105090. https://doi.org/10.1016/J.APPLANIM.2020.105090.
64. Lulijwa, R.; Rupia, E.J.; Alfaro, A.C. Antibiotic Use in Aquaculture, Policies and Regulation, Health and Environmental Risks:
A Review of the Top 15 Major Producers. Rev. Aquac. 2020, 12, 640–663. https://doi.org/10.1111/raq.12344.
65. Devos, S.; Stremersch, S.; Raemdonck, K.; Braeckmans, K.; Devreese, B. Intra-and Interspecies Effects of Outer Membrane Ves-
icles from Stenotrophomonas maltophilia on β-Lactam Resistance. Antimicrob. Agents Chemother. 2016, 60, 2516–2518.
https://doi.org/10.1128/AAC.02171-15.
66. Bielaszewska, M.; Bauwens, A.; Kunsmann, L.; Karch, H.; Mellmann, A. Antibiotic-Mediated Modulations of Outer Membrane
Vesicles in Enterohemorrhagic Escherichia coli O104:H4 and O157:H7. Antimicrob. Agents Chemother. 2017, 61, e00937–17.
https://doi.org/10.1128/AAC.00937-17.
67. Vanden Bergh, P.; Heller, M.; Braga-Lagache, S.; Frey, J. The Aeromonas salmonicida Subsp. Salmonicida Exoproteome: Global
Analysis, Moonlighting Proteins and Putative Antigens for Vaccination against Furunculosis. Proteome Sci. 2013, 11, 1–12.
https://doi.org/10.1186/1477-5956-11-44.
68. Devos, S.; Van Putte, W.; Vitse, J.; Van Driessche, G.; Stremersch, S.; Van Den Broek, W.; Raemdonck, K.; Braeckmans, K.;
Stahlberg, H.; Kudryashev, M.; et al. Membrane Vesicle Secretion and Prophage Induction in Multidrug-Resistant Stenotropho-
monas maltophilia in Response to Ciprofloxacin Stress. Environ. Microbiol. 2017, 19, 3930–3937. https://doi.org/10.1111/1462-
2920.13793.
69. Pérez-Cruz, C.; Carrión, O.; Delgado, L.; Martinez, G.; López-Iglesias, C.; Mercade, E. New Type of Outer Membrane Vesicle
Produced by the Gram-Negative Bacterium Shewanella vesiculosa M7T: Implications for DNA Content. Appl. Environ. Microbiol.
2013, 79, 1874–1881. https://doi.org/10.1128/AEM.03657-12.
70. Zingl, F.G.; Kohl, P.; Cakar, F.; Leitner, D.R.; Mitterer, F.; Bonnington, K.E.; Rechberger, G.N.; Kuehn, M.J.; Guan, Z.; Reidl, J.;
et al. Outer Membrane Vesiculation Facilitates Surface Exchange and In Vivo Adaptation of Vibrio cholerae. Cell Host Microbe
2020, 27, 225-237.e8. https://doi.org/10.1016/j.chom.2019.12.002.
71. Ebanks, R.O.; Dacanay, A.; Goguen, M.; Pinto, D.M.; Ross, N.W. Differential Proteomic Analysis of Aeromonas salmonicida Outer
Membrane Proteins in Response to Low Iron and in Vivo Growth Conditions. Proteomics 2004, 4, 1074–1085.
https://doi.org/10.1002/pmic.200300664.
72. Menanteau-Ledouble, S.; Kattlun, J.; Nöbauer, K.; El-Matbouli, M. Protein Expression and Transcription Profiles of Three Strains
of Aeromonas salmonicida Ssp. Salmonicida under Normal and Iron-Limited Culture Conditions. Proteome Sci. 2014, 12, 29.
https://doi.org/10.1186/1477-5956-12-29.
73. Menanteau-Ledouble, S.; El-Matbouli, M. Antigens of Aeromonas salmonicida Subsp. Salmonicida Specifically Induced In Vivo in
Oncorhynchus mykiss. J. Fish Dis. 2016, 39, 1015–1019. https://doi.org/10.1111/jfd.12430.
74. Barnes, A.C.; Horne, M.T.; Ellis, A.E. Effect of Iron on Expression of Superoxide Dismutase by Aeromonas salmonicida and Asso-
ciated Resistance to Superoxide Anion. FEMS Microbiol. Lett. 1996, 142, 19–26. https://doi.org/10.1111/j.1574-6968.1996.tb08401.x.
75. Lim, C.K.; Hassan, K.A.; Tetu, S.G.; Loper, J.E.; Paulsen, I.T. The Effect of Iron Limitation on the Transcriptome and Proteome
of Pseudomonas fluorescens Pf-5. PLoS ONE 2012, 7, e39139. https://doi.org/10.1371/journal.pone.0039139.
76. Lan, Y.; Zhou, M.; Li, X.; Liu, X.; Li, J.; Liu, W. Preliminary Investigation of Iron Acquisition in Hypervirulent Klebsiella pneu-
moniae Mediated by Outer Membrane Vesicles. Infect. Drug Resist. 2022, 15, 311–320. https://doi.org/10.2147/IDR.S342368.
Microorganisms 2022, 10, 1735 24 of 24
77. Groberg Jr., W.J.; McCoy, R.H.; Pilcher, K.S.; Fryer, J.L. Relation of Water Temperature to Infections of Coho Salmon (Oncorhyn-
chus kisutch), Chinook Salmon (O. tshawytscha), and Steelhead Trout (Salmo gairdneri) with Aeromonas salmonicida and A. hydroph-
ila. J. Fish. Res. Board Can. 1978, 35, 1–7. https://doi.org/10.1139/f78-001.
78. Knøchel, S. Effect of Temperature on Hemolysin Production in Aeromonas Spp. Isolated from Warm and Cold Environments.
Int. J. Food Microbiol. 1989, 9, 225–235. https://doi.org/10.1016/0168-1605(89)90092-5.
79. Frias, A.; Manresa, A.; de Oliveira, E.; López-Iglesias, C.; Mercade, E. Membrane Vesicles: A Common Feature in the Extracel-
lular Matter of Cold-Adapted Antarctic Bacteria. Microb. Ecol. 2010, 59, 476–486. https://doi.org/10.1007/s00248-009-9622-9.
80. Vincent, A.T.; Charette, S.J. To Be or Not to Be Mesophilic, That Is the Question for Aeromonas salmonicida. Microorganisms 2022,
10, 1–8. https://doi.org/10.3390/microorganisms10020240.
81. Dowling, P.M. Chloramphenicol, Thiamphenicol, and Florfenicol. In Antimicrobial Therapy in Veterinary Medicine; Wiley: Hobo-
ken, NJ, USA, 2013; pp. 269–277.
82. Desbois, A.P.; Cook, K.J.; Buba, E. Antibiotics Modulate Biofilm Formation in Fish Pathogenic Isolates of Atypical Aeromonas
salmonicida. J. Fish Dis. 2020, 43, 1373–1379. https://doi.org/10.1111/jfd.13232.
83. Perez-Riverol, Y.; Bai, J.; Bandla, C.; García-Seisdedos, D.; Hewapathirana, S.; Kamatchinathan, S.; Kundu, D.J.; Prakash, A.;
Frericks-Zipper, A.; Eisenacher, M.; et al. The PRIDE Database Resources in 2022: A Hub for Mass Spectrometry-Based Prote-
omics Evidences. Nucleic Acids Res. 2022, 50, D543–D552. https://doi.org/10.1093/NAR/GKAB1038.
