The relationship between toxicity and mixotrophy in bloom dynamics of
the ichthyotoxic Prymnesium parvum
Konstantinos Anestis1*, Sylke
Wohlrab1,2, Elisabeth Varga3, Per
Juel Hansen4 and Uwe John1,2*
1 Alfred Wegener Institute, Helmholtz Center for Polar
and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
2 Helmholtz Institute for Functional Marine
Biodiversity at the University of Oldenburg (HIFMB), Ammerländer
Heerstraße 231, 26129, Germany
3 Department of Food Chemistry and Toxicology, Faculty
of Chemistry, University of Vienna, Währinger Straße 38-40, 1090 Vienna,
Austria
4 Marine Biology Section, University of Copenhagen,
Strandpromenaden 5, 3000 Helsingør, Denmark
*Corresponding authors:
Konstantinos Anestis (kanestis@awi.de)
Uwe John (uwe.john@awi.de)
Keywords: HABs; haptophytes; marine toxins; polyketides;
microbial ecology; species interactions
ABSTRACT
Toxin production in planktonic protists is widespread and comprises an
effective mechanism to eliminate competitors or grazers. Toxins released
into the water can mediate the immobilization of prey for subsequent
consumption or can mediate the lysis and uptake of the released
nutrients. For the worldwide-distributed ichthyotoxic and mixotrophic
haptophyte Prymnesium parvum , the relationship between toxin
production; impact on co-occurring species, and mixotrophy remains
blurred. In the current study, we show that changes in salinities (5 vs
30), phosphorus (P) availabilities (P-replete vs P-deplete) and cell
densities affect growth, toxicity and mixotrophy in P. parvum .
Cell density positively affected cellular toxin content by a factor of
up to 10. Low salinity resulted in a higher mortality of the cryptophyte
prey Teleaulax acuta , with ~80% of cells being
lysed after 2 h of incubation. However, phagotrophic rates were higher
in P-deplete conditions, independent of the salinity. Transcriptomic
analysis of the monocultures revealed the up-regulation of genes
involved in endocytosis under either low salinity and phosphorus,
suggesting that this process is evolutionarily conserved, triggered by
environmental stressors and independent of prey presence. Polyketide
synthase genes, potentially involved in toxin biosynthesis, exhibited
distinct expression patterns, depending on the physiological status,
toxicity and with generally higher expression under the high cell
density conditions. Overall, our study contributes to a better
understanding of the dynamics between the two critical processes of
toxin production and mixotrophy, and has important implications for
bloom formation and its maintenance in this ecologically important
species.
INTRODUCTION
Harmful algal blooms (HABs) are characterized by a rapid proliferation
with detrimental effects on the ecosystem. The causes of such plankton
blooms are variable and can be of both anthropogenic and environmental
origin (Lewitus et al. , 2012). Among the best studied driving
factors is eutrophication due to the inflow of dissolved nutrients,
which can be subsequently used by phototrophic plankton (both
prokaryotic and eukaryotic) for rapid growth (Heisler et al. ,
2008). The increasing global occurrence of HABs (Anderson et al. ,
2012; Gobler et al. , 2017) has additionally been suggested to be
a consequence of climate change (Gobler, 2020).
Haptophytes are a diverse group of (nano)plankton with a worldwide
distribution and important contributions to primary production and
biogeochemical cycles (Edvardsen et al. , 2016). Known
bloom-forming haptophytes include Chrysochromulina leadbeateri ,Prymnesium polylepis , Prymnesium parvum andPhaeocystis spp .. HABs often cover large coastal areas that cause
mortalities of fish and other marine fauna and/or damage to ecosystem
function, e.g., disruption of food webs or oxygen depletion, or loss of
recreational opportunities due to biofouling of beaches and coastal
waters (Karlson et al. , 2021). Massive fish mortalities may be
attributed to known ichthyotoxins or unknown compounds (Andersenet al. , 2015; Mardones et al. , 2019). Several fish killing
HAB events have been recorded world-wide in recent years (Hallegraeffet al. , 2021) and are often associated with haptophytes (Bresnanet al. , 2021; Karlson et al. , 2021; John et al. ,
2022). In most cases in Scandinavia, massive fish-killing events have
been directly linked to blooms of marine haptophytes, particularly
members of the genera Prymnesium and Chrysochromulina .
Many HAB forming species, including many haptophytes, are mixotrophic,
i.e., they are able to combine the two trophic modes of
phagotrophy/osmotrophy and phototrophy in order to cover their
nutritional needs (Burkholder et al. , 2008; Unrein et al. ,
2013; Flynn et al. , 2018). This is especially the case in
eutrophic ecosystems, where growth rates of mixoplanktonic species
(Flynn et al. , 2019) can be affected by both the increased
dissolved nutrients and the availability of algal and bacterial prey
(Burkholder et al. , 2008). Additionally, mixotrophy can be highly
advantageous under low or imbalanced nutrient conditions, as it can be
an efficient mechanism to compensate for limiting nutrients (Stoeckeret al. , 2017).
The ichythyoxic HAB species P. parvum is known to produce toxic
compounds, collectively called prymnesins. These cause lysis/death of
competitors and grazers, as well as lysis of fish gill cells. Prymnesins
are large ladder-frame polyketide compounds, of which three types are
described, A-, B- and C- types, each differing in the length of the
carbon backbone (Igarashi et al. , 1999; Rasmussen et al. ,
2016). The production of lytic compounds by P. parvum , whether
studied using bioassays or by actual measurements of prymnesins, are
known to be influenced by phosphorus (P) availability, light and
temperature ((Beszteri et al. , 2012; Qin et al. , 2020;
Taylor et al. , 2020, 2021; Medić et al. , 2022). Most
probably, prymnesins are produced by polyketide synthases (PKS) of the
modular type I (Anestis et al. , 2021). The release of lytic
compounds by P. parvum into the surrounding water has been shown
to assist feeding, via immobilization and lysis of the prey, which
allows uptake of nutrients through either osmotrophy or phagotrophy
(Skovgaard and Hansen, 2003; Tillmann, 2003).
P. parvum typically form blooms in estuaries at low salinity
(2-8), despite the fact that this species grows fine in the salinity
range of 0.5-45 (Edvardsen and Paasche, 1998; Barone et al. ,
2010). Why it preferably blooms at low salinities is unknown, but could
be due to input of organic material from freshwaters, or simply because
very few species can thrive at these salinities (Brand, 1984).
Additional factors that influence the bloom dynamics of this species
include the mediation of viruses that interact with components of their
cellular membrane (Wagstaff et al. , 2018, 2021).
In this study, P. parvum strain UIO223 was used to investigate
the combinatory effects of bloom formation supporting conditions i.e.,
low salinity, P limitation, and cell density. More specifically, we used
two salinity (salinity of 5 vs salinity of 30) and P (P-replete vs
P-deplete) treatments to examine cellular toxin content and toxin
profile, phagotrophy, and metabolic processes related to adaptation
under the different treatments. The metabolic processes were related to
growth, potential to mixotrophy (expression of phagotrophy related genes
in monocultures) and biosynthesis of polyketides. Additionally, we
sampled at two cell densities (low vs high) to investigate the processes
that support the maintenance of a bloom with high cell density. We
hypothesized that A) P. parvum will increase its toxin content
and production at low salinity, and low P concentrations in combination
with increased phagotrophy. B) cellular and metabolic processes deduced
from gene expression analyses will depict the corresponding cellular
adjustment; C) P. parvum needs to reallocate cellular resources
to maintain growth under these limiting conditions under high cell
density (bloom concentration), which has an impact on levels of
phagotrophy.
MATERIALS AND METHODS
Experimental set-up, sampling and incubations with prey
Phosphorus replete cultures of P. parvum strain UIO-223 were
grown in standard K-medium with PO43-concentration of 36 μM, while for the P deplete conditions,
PO43- was added at a final
concentration of 2.4 μM. Culture medium with a salinity of 5 was
obtained by diluting sterile filtered seawater with MilliQ water. The
concentration of inorganic carbon in the low salinity medium was
restored by adding 1 M NaHCO3 in 1 mL L-1 of medium.
Prior to establishing the experimental cultures, the culture was
rendered axenic using a cocktail of antibiotics (165 μg
mL-1 ampicillin, 33.3 μg mL-1gentamicin, 100 μg mL-1 streptomycin, 1 μg
mL-1 chloramphenicol, 10 μg mL-1ciprofloxacin). The treatment with antibiotics lasted 4 days and was
performed twice with an interval of one week. The axenicity of the
cultures was examined by fluorescence microscopy after staining with
4′,6-diamidino-2-phenylindole (DAPI).
Four replicate cultures were established for each combination of
salinity (30 and 5) and phosphorus (P replete and P deplete; 2x2
factorial design). All cultures were kept in 17 °C in 16:8 light:dark
cycle and under a photon flux density of 80 μmol photons
m-2 s-1. The cultures were bubbled
to avoid carbon deficiency. The pH of the cultures was monitored daily,
and it never exceeded 8.5. All cultures were sampled at both low cell
density and high cell density.
Cell enumeration was performed using a Multi-Sizer III particle counter
(Beckman-Coulter, Fullerton, USA). Phagotrophy was estimated usingTeleaulax acuta (SCCAP K-1486) as prey, grown under the same
condition as P. parvum . The initial cell concentration for the
incubation was 30*103 cells mL-1 and
the ratio between P. parvum and prey was 1:1, following the
recommendation of the existing literature (Lundgren et al. ,
2016). To estimate phagotrophy, 2 mL of culture were fixed with Lugol
(final concentration of 2%, v:v), and inspected in a Sedgewick Rafter
chamber under an Axio Vert A1 Microscope equipped with a Colibri 7
(Zeiss) light source.
Physiological parameters sampling and processing
Samples for inorganic nutrient measurements were taken by filtrating 15
mL of culture using 0.2 μM Millipore filters in order to eliminate
cells. The nutrients that were measured included nitrate, nitrite, and
phosphate, and were analyzed with a continuous-flow autoanalyzer
(Evolution III, Alliance Instruments, Freilassing, Germany). The
protocols that were used are standard for the quantification of
nitrite/nitrate (Armstrong et al. , 1967) and phosphate in
seawater (Eberlein and Kattner, 1987).
Samples for POC and PON analysis were collected by filtering 30 mL of
culture through precombusted glass microfiber filters (Whatman GF/F,
Maidstone, UK; nominal pore size: 0.7 µm) and were immediately frozen in
pre-combusted glass vials until further analysis. The filters were dried
at 50 °C overnight, acidified with 300 µL 0.2 N HCl, and again dried
overnight at 50 °C. The acidified and dried filters were packed in tin
foil and analyzed on a Euro Elemental Analyzer 3000 CHNS-O (HEKAtech
GmbH, Germany).
Samples for Chl-a concentrations were taken by filtering 15 mL of
culture through 22 mm glass microfiber filters (Whatman GF/F, Maidstone,
UK; nominal pore size: 0.7 µm). The sample filters were frozen at −80 °C
until laboratory analysis. Extraction was performed by sonication of
filters in 10 mL 90% acetone and then incubated overnight in darkness
at 4 °C. The extract was centrifuged at 3020 × g for 10 min, and the
fluorescence of the supernatant was determined at 665 nm (TD-700
fluorometer, Turner Designs, Sunnyvale, USA).
Toxin extraction and quantification was performed according to a
previously described protocol (Svenssen et al. , 2019), with small
modifications as described in Anestis et al. , 2021. In brief,
cells were collected on 22 mm glass microfiber filters (Whatman GF/F,
Maidstone, UK; nominal pore size: 0.7 µm). The biomass on each filter
was extracted two times with 20 mL MeOH each using an ultrasonic batch
for 30 min with a centrifugation step in between (4300 ×g for 15 min at
4 °C). The combined extract (40 mL) was evaporated to dryness using a
CentriVap Benchtop Vacuum Concentrator (Labconco Corporation, Kansas
City/ MO, USA) at 35 °C. The samples were reconstituted with 1 mL
methanol:H2O (90:10, v:v) and short-time ultrasonic bath
treatment. HPLC-FLD measurements were performed after derivatization
with the AccQ-Tag Fluor Reagent Kit (Waters Cooperation, Milford/MA,
USA) with a 1200 HPLC system (Agilent Technologies, Waldbronn, Germany)
using fumonisins B1 and B2 as external calibrants due to the lack of
standards and the obtained results are an approximation of the prymnesin
content in the samples. To confirm the presence of prymnesins and
identify the specific prymnesin analogues, HPLC-HRMS-measurements were
performed using a 1290 UHPLC system coupled to a 6550 iFunnel QTOF LC/MS
(both from Agilent Technologies). Chromatographic separation was
achieved with a Kinetex F5 (2.1 × 100 mm, 2.6 μm, Phenomenex,
Aschaf-fenburg, Germany) column using a water-acetonitrile gradient
(eluent A: H20, eluent B: acetonitrile:
H2O (90:10, v:v)), both eluents contained 1 mM ammonium
formate and 0.1% formic acid. The mass spectrometer was operated in the
positive ionization mode in a scanning range of m/z 50 to 1700 with 3
scans per second.
RNA extraction, library construction and sequencing
Cells for RNA extraction were harvested by centrifugation at 1500 × g
for 10 min and the cell pellet was transferred to 1 mL pre-chilled
TriReagent mixed with glass beads. RNA isolation was performed as
described in Wohlrab et al. , (2017). Libraries for sequencing
were prepared using the Truseq Stranded mRNA Samples Prep LS Protocol
(Illumina GmbH, Berlin, Germany) and 1 μg of RNA as input. The
paired-end cDNA libraries (2x150 bp) were sequenced on the Illumina
Nextseq 500 machine (Illumina, San Diego, USA) and a high-output kit v2
(2 x 150 cycles).
Quality control of sequencing data, de novo assembly and annotation
Prior to assembly, the raw reads were pre-processed using Trimmomatic
v.0.39 (Bolger et al. , 2014) and reads contaminated with adapters
or quality scores of <5 were trimmed using the default
settings and only paired-end reads were retained. Inspection with FastQC
assured the high quality of the reads and absence of adapter
con-tamination before proceeding to the construction of the de novo
assembly (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
The reference transcriptome was constructed using Trinity (v2.11.0) with
minimum contig length of 300 bp (Haas et al. , 2013). To reduce
redundancy due to the assembling method, the output contigs were
clustered together with a similarity threshold of 0.95 using the
cd-hit-est command of CD-hit and the longest representative for each
cluster transcript was kept (Fu et al. , 2012).
Gene annotation was performed using the Trinotate functional annotation
suite (version 3.2.1; Grabherr et al., 2011). Transdecoder (v5.5.0) was
used for detecting open reading frames (ORFs) for each gene
(https://github.com/TransDecoder/TransDecoder). The gene sequences were
aligned against the UniprotKB/Swiss-Prot (release 2021_03) using
diamond with BLASTX and BLASTP as an option (blast version 2.10.1) and
the best hit for each query was retained with an e value of <1
e-9. Further annotation information, like entries from
the KEGG and the assignment of Gene Orthology (GO) terms were retrieved
from the UniprotKB database.
Gene expression analysis
Quantification of gene expression was performed by mapping the
paired-end reads in CLC Genomics Workbench 20, using the default
settings. The resulting gene count matrix was normalized using the
variance stabilizing transformation function of the Deseq2 package (Loveet al. , 2014) and multiple comparison tests with three-way
analysis of variance (ANOVA) were performed in order to define the
effect of salinity, phosphorus and cell density in gene expression. For
genes with significant interactions only, single t-tests were applied to
identify the conditions causing expression changes. For every gene, a
factor was considered to have a significant effect on the expression
variance when satisfying an adjusted p value threshold of
<0.01 and fold change >1.5. P values were
adjusted by applying the Benjamini-Hochberg false discovery rate for
multiple test correction (Benjamini and Hochberg, 1995). For the
visualization of the intersecting sets of differentially expressed
genes, the R package UpSetR was used (Conway et al. , 2017).
Statistical analysis
Statistical analysis of the physiological parameters was performed using
three-way analysis of variance (ANOVA) and the factors salinity,
phosphorus and cell density. The normality of the distribution of the
residuals was checked with the Shapiro-Wilk test, and an appropriate
transformation of the data (logarithmic or square transformation) was
applied to achieve p > 0.05. Pairwise comparisons were
examined using Tukey’s HSD (honestly significant difference) test. All
analyses were performed using the R software.
RESULTS
Growth physiology
For the first 3 days of the experiment, growth rates for cultures at low
salinity varied from 0.86 to 0.92 μ d-1 in comparison
to 0.72 to 0.75 μ d-1 for cells growing at high
salinity, irrespective of initial P treatment (p-value < 0.01;
Table S1). Subsequently, growth rates gradually decreased for all
treatments, with 0.16 to 0.19 μ d-1 at the final day
of the experiment for the non-limited cultures, while complete
inhibition of growth was observed in the P-limited cultures (Figure 1a;
Figure S1). In the low phosphorus (LP) treatments growth stopped at day
7, and the cell concentration remained stable for the following 2 days,
indicating P limitation of growth (~450,000 cells
mL-1; Figure 1a-b). Extra P was added at day 9 to the
LP treatments, which led to an immediate increase in cell concentration.
The addition of extra P in this treatment was done to validate that P
was the limiting factor and that growth was affected only by its
depletion . In non-limited P cultures, cell concentration increased
until the end of the experiment at day 13 and reached to 3.5
106 cells mL-1 and 3.9
106 cell mL-1 for high salinity and
low salinity respectively (Figure 1a).
Particulate organic nutrients (C:N) were measured to gain understanding
of the elemental composition of the cells under the different
treatments. Under low cell density, the per cell quota in POC was
affected by salinity with 59.9-61.2 pgC cell-1 and
42.1-43 pgC cell-1 for high and low salinity cells
respectively (Figure 1c). When P depletion was reached these values were
lower for the P replete cells with 16.5-21.6 pgC
cell-1, in contrast to 29.8-28.7 pgC
cell-1 observed in the P depleted cells (Figure 1c).
All salinity, phosphorus and cell density treatments had statistically
significant effects on the cellular particulate organic carbon (POC)
content (Table S2). In general, cellular POC was higher in low cell
density cultures for all treatments (pairwise comparisons with p
< 0.005; Table S2). At low cell densities, the low salinity
treatments had the lowest cellular POC content, while at the high cell
densities, P-starved cells had a significantly higher cellular POC
content. In accordance with the decrease in cellular POC content, a cell
density dependent decrease in cellular particulate organic nitrogen
(PON) content was also observed (Figure 1d). Salinity and P as single
factors seemed to have no statistically significant effect on cellular
PON content; significant differences were, however, observed in
combinations with salinity and P. The decrease in cellular PON was
higher than in cellular POC, indicated by the cellular C:N
stoichiometry; high cell density cultures had a significantly higher C:N
ratio (p <0.001; Table S2) compared to low cell density
cultures (Figure 1e). Cells grown at low salinity, had consistently
lower C:N ratios compared to those grown at high salinity. Cellular
chlorophyll-a (Chl-a ) content was reduced by
~2.5-fold at the highly dense cultures as compared to
low cell density cultures, this was consistent for all treatments (p
<0.001; Table S2; Figure 1f). The combination of P-depletion
and high cell density resulted insignificantly higher cellular
Chl-a (p<0.001; Table S2).
Prey ingestion
Teleaulax acuta was provided as prey and its mortality and
phagotrophy by P. parvum was measured as the percentage of cells
containing food vacuoles after 2 h, 6 h, 24 h, 48 h and 72 h of
incubation with the prey. T. acuta cells showed higher mortality
when incubated with low salinity P. parvum cultures, and
independently of phosphorus condition, with ~80% being
lysed 2 h after the beginning of the incubation with P. parvum(Figure 2d). Decrease in T. acuta concentration at 2 h were
observed also under the high salinity condition, but was considerably
less extent than in low salinity (Figure 1c). For the low salinity/P
replete treatments, complete prey removal was observed 24 h after the
beginning of the incubations, while for the low salinity/P deplete
treatments complete prey removal was observed at 72 h (Figure 2c). For
the high salinity treatments, T. acuta mortality was lower, but
complete prey removal was observed at 72 h in all cases. The growth of
monocultures of T. acuta growing under the same culturing media
used for P. parvum was monitored (Figure S2).
P. parvum cells containing a food vacuole were first observed
after 6 h (Figure 2d). Phagotrophy was significantly induced in P
starved conditions, independently of salinity, with an average of 11 ± 1
% of the total cells containing a food vacuole from 6 h until 48 h. In
the P replete treatments, P. parvum phagotrophy was less with a
maximum of < 6 % of the total cells feeding at some time
point. The number of cells with a food vacuole considerably decreased
for all treatments from 48 h to 72 h, consistent with the depletion of
prey at 72 h. Interestingly, even though the highest mortality rates ofT. acuta were observed at the low salinity, in the P-replete
condition, phagotrophy rates were very low. Growth rates recorded forP. parvum grown with prey were lower than the growth rates of
monocultures for the high salinity treatments, which was not the case at
the low salinity treatments, where growth rates of monocultures were
similar to the cultures with prey addition (Table S1, Figure S3).
Toxin content and profile
Cellular prymnesin contents in P. parvum were significantly
higher at high cell density compared to at low cell density for all
treatments (p < 0.0001, Table S2). Cell density and P
depletion both had a statistically significant effect in explaining the
variance in cellular prymnesin contents (p < 0.001), as both
factors led to increases in prymnesin content by
~8.3-fold and ~2.4-fold respectively
(Figure 2a). Salinity had statistically significant effects only in
combination with P concentration and cell density (Table S2). In low
cell density culture conditions no significant differences in toxin
contents were observed. The highest amount of cellular toxin content was
observed among high density and P starved conditions (p
<0.005).
The percentage contribution of the prymnesin analogs to the overall
prymnesin quantity, varied among the treatments, and was affected by all
factors of the experiment; salinity, P and incubation time (Figure 2b).
The four analogs that were detected differ in presence or absence of
attached sugars including a pentose, a hexose or both of these two. The
main analog for the majority of time points and treatments was the
prymnesin B-type containing one chlorine and one pentose moiety, with
the exception of the low salinity/P-deplete cells for which the
prymnesin without attached sugar accounted for about half of the overall
toxins at high cell density. The prymnesin analog without sugar showed a
general increasing pattern in the low salinity treatment and especially
in high density. The prymnesin analog containing both pentose and hexose
showed consistently low contribution to the overall prymnesin content,
however, it accounted for 9 ± 1% and 7 ± 2% for the P starved cells
under high salinity and low salinity, respectively. The hexose
containing prymnesin analog was mainly present in the low salinity and P
starved cells with a contribution of 11 ± 5%.
Gene expression analyses
The transcriptome of P. parvum consisted of 103,051 contigs,
which resulted after their clustering with 95% similarity (Figure 3a).
Gene expression differences were ana-lyzed via Principal Components
Analysis (PCA) for assessing the driving experimental factors for
changes in gene expression (Figure 3b). Salinity induced the big-gest
change in the transcriptome under low cell density. For the high cell
density cultures, P-replete and P-deplete culture samples formed two
distinct clusters. Salinity explained the expression variance of 2233
transcripts, followed by cell density with 1622 transcripts, the
interaction of salinity and P with 1041 and the interaction of salinity
and cell density with 1125 transcripts (Figure 3c). Phosphorus as a sole
parameter influenced the expression of 203 transcripts, while the number
of transcripts increased to 988 for the interaction between P and cell
density. The number of differentially ex-pressed genes (DEGs) with a
Kyoto Encyclopedia of Genes and Genomes (KEGG) identifier for which
salinity had an effect was 324, followed by cell density with 309 and P
with 225 (Figure 4a-c).
Growth and cell density effects
Carbohydrate metabolism, including anabolic and catabolic processes, are
significantly influenced by the salinity treatment, with genes involved
in catabolic processes being significantly up-regulated under low
salinity (Table 1). Significantly overexpressed genes under low salinity
included glyceraldehyde 3-phosphate dehydrogenase
(contig51264_c0_g1_i1) and pyruvate dehydrogenase E1 component
(contig50014_c0_g1_i1), which showed 31-fold and 30-fold increase
respectively. Glyceraldehyde 3-phosphate dehydrogenase catalyzes the
conversion of glyceraldehyde 3-phosphate to 1,3-bisphosphoglycerate
which can subsequently form pyruvate. Pyruvate in turn can be converted
to acetyl-CoA and the production of energy in the form of NADH.
Acetyl-CoA can subsequently enter the citric acid cycle and produce
further energy. Additional overexpressed genes that are involved in
glycolysis included pyruvate dehydrogenase E2 component
(contig6111_c0_g1_i19) and glucose-6-phosphate 1-epimerase
(contig1336_c0_g1_i33) with 2-fold and 6-fold increase respectively.
Enzymes involved in valine, leucine and isoleucine degradation, such as
isovaleryl-CoA dehydrogenase (contig51612_c0_g1_i1) and
malonate-semialdehyde dehydrogenase (contig37437_c0_g1_i1) were
up-regulated by 77-fold and 46-fold respectively.
On the other hand, malate synthase (contig7939_c0_g1_i20), which
participates in the anabolic process of glyoxylate cycle, showed a
28-fold decrease under low salinity, highlighting the re-arrangement of
cellular metabolism in favor of energy production rather than energy
storage. Down-regulation under low salinity was also observed for genes
encoding for glucokinase (contig9551_c0_g1_i5), phosphoglucomutase
(contig10485_c0_g1_i71) and phosphoglycerate kinase
(contig4027_c0_g1_i11).
P-starvation and cell density induced changes in the expression of genes
involved in energy metabolism (Figure 4a). In P depleted cells, ten
genes involved in energy metabolism were down-regulated while five genes
were up-regulated. Processes related to translation (38 down-regulated
vs 9 up-regulated) and transcription (18 down-regulated vs 3
up-regulated) were strongly down-regulated under P depletion (Figure
4a). The cell density effect in growth was also depicted in energy
metabolism, with 27 genes being down-regulated in contrast to 3 that
were up-regulated (Figure 4c).
Phagotrophy
To study the potential for phagotrophy in monocultures of P.
parvum we examined the expression pattern of genes involved in
endocytosis, phagosome, lysosome and peroxisome formation (Figure 5).
Genes involved in endocytosis were mainly up-regulated under low
salinity and P starvation (Figure 5). More specifically, ten genes were
up-regulated under either low salinity or P starvation. Concerning cell
density, two genes were differentially expressed and all up-regulated in
low cell density. The expression of 16 genes involved in lysosomes,
resulted in two distinct clusters, with eight genes presenting a higher
expression under either low salinity or phosphorus depletion (Figure 5).
No clear patterns in relationship to the treatments could be observed
for genes involved in the phagosome or peroxisome formation.
Toxin production
The expression dynamics of PKSs were examined in order to check their
expression profile under the different treatments. The expressed PKSs
formed 10 distinct clusters (clusters A-J) (Figure 6). The expression of
PKSs showed higher expression values under the high cell density (bloom
conditions) conditions, with the exception of the low salinity and
P-replete condition. Clusters D, E, I and J showed the higher over-all
expression values, and mainly consisted of modular Type I PKSs. The
length and functional domain organization of contigs belonging to the
clusters D and I are provided in Table 2. The expression of contig
UIO223_409_c0_g1_i1 was consistently high across all treatments, but
the highest expression value was observed under P-starvation and
independently of salinity. This contig is characterized by the presence
of a polyketide-type polyunsaturated fatty acid synthase (pfaA), which
are involved in the biosynthesis of omega-3 polyunsaturated fatty acids.
The effect of P starvation and higher expression of PKSs under this
condition was more visible in clusters F and H, and especially for the
high salinity treatment. In cluster D, the expression of three contigs
(UIO223_7525_c0_g1_i2, UIO223_34765_c0_g1_i1 and
UIO40_c0_g1_i4) was higher under P starvation and low cell density.
DISCUSSION
Cell growth and physiological responses to phosphorus depletion and low
salinity
P. parvum is an euryhaline species with the ability to grow in a
wide range of salinities from 0.5 to 45 (Edvardsen and Paasche, 1998;
Beszteri et al. , 2012; Granéli et al. , 2012). Much
research has been conducted on the relationship between salinity and
blooming potential in P. parvum . In the field, blooms of P.
parvum usually occur in estuaries with low salinity (2-8), while in
some cases salinity can be even <2 (Richardson and Patiño,
2021). In the lab, growth rates under different salinities are variable
and no clear relationship can be observed between these two parameters
(Roelke et al. , 2011; Patiño et al. , 2014; Rashel and
Patiño, 2017), thus, highlighting the importance of culturing conditions
and the different responses of P. parvum isolates. In the current
study, growth rates for P. parvum growing under low salinity
presented statistically significant higher growth rates.
Cellular particulate organic carbon and nitrogen contents were
negatively influenced by cell density, irrespective of salinity and
inorganic phosphorus concentration. The POC per cell measurements for
the P deplete cells were similar to the quota of 24.2 pg
cell-1 previously reported for P depleted P.
parvum (Lundgren et al. , 2016). It is a possibility that the
general decrease in POC content in high cell density cultures (not
nutrient limited) could be attributable to lower dissolved inorganic
carbon (DIC) availability due to removal of DIC at high cell density.
Even though DIC was not measured in this study, the pH of the cultures
was controlled by bubbling and we have no indications that cells were
carbon limited. Also, the decrease in cellular POC was accompanied by a
decrease in cellular PON, suggesting a general decrease in cell size.
These findings support the concept that cellular stoichiometry and
growth rates are considered to be strictly related, with decrease in
carbon content when cells present lower growth rates (Garcia et
al. , 2016; Moreno and Martiny, 2018)
Genes involved in carbohydrate metabolism seemed to be mainly affected
by salinity and cell density, suggesting a general re-adjustment of
carbon-related pathways under these conditions. The expression patterns
of carbohydrate metabolic genes suggest increased carbon turnover
related to the growth rates of cells under the different salinity and
cell density conditions. To fulfill the energy and carbon units demands
key enzymes involved in glycolysis and pyruvate metabolism were
significantly up-regulated. Furthermore, the glyoxylate cycle, a way of
bypassing the two oxidative decarboxylation reactions of the TCA cycle
and directly converts isocitrate through isocitrate lyase and malate
synthase into malate and succinate, showed a decrease in gene
expression. Carbohydrate rearrangement seems to be a critical factor
under different salinity treatments, as it is also related to the
production of osmolytes for the balance of osmotic pressure in cells
(Harding et al. , 2016, 2017).
Prymesin production, cell lysis and phagotrophy
Prymnesins are currently considered to be the toxins in P. parvumresponsible for the lytic effects observed on other organisms (Rasmussenet al. , 2016; Binzer et al. , 2019). Recent advances in
prymnesin quantification have facilitated our understanding of toxin
dynamics, production and release in the environment. Svenssen et
al. , 2019 developed an indirect method for the estimation of prymnesin
type B and found that the majority of the toxin is intracellular.
Moreover, the combination of bioassays and biochemical approaches have
reinforced the idea that prymnesins are the actual factors behind acute
toxicity.
In the present study, the intracellular prymnesin toxin content (cell
quota) was significantly higher in high cell density cultures,
suggesting cell density or growth rate (accumulative) dependent
mechanisms that define the cellular toxin content. This apparent
stimulation of prymnesin production as the cultures grow dense has never
been observed before in P. parvum or any other algae producing
lytic compounds, and this discovery needs further scrutiny. Increased
production and release of lytic toxins in dense populations will be
favorable for the alga, because at low P. parvum cell
concentrations there will be not benefits of such compounds, given their
concentration dependent mode of action (Tillmann, 2003).
In the present study, prey mortality was significantly higher at low
salinity, irrespectively of the nutrient conditions. This observation
did not match with the measurements of prymnesin production. The
experimental set-up and results do, however, not allow us to distinguish
between potential higher toxicity due to increased release of prymnesins
in the medium at low salinity, or higher prey sensitivity due to low
salinity effects. Additionally, the toxin profile was also influenced by
salinity and P, as the relative composition of prymnesin analogues was
affected. Consequently, we cannot rule out, that the different analogues
could perform various levels of lytic activity or that other unknown
compounds may be involved in prey cell lysis.
The highest feeding rates were observed in P-deplete treatments, while
the lowest feeding rates were observed at high salinity and P-replete
treatments. At low salinity, the rates of prey mortality were initially
very high. This could have led to low feeding rates because the prey
cells had lysed before P. parvum had the opportunity to ingest
them, but they may have benefited from osmotrophy of newly released or
produced DOM of the lysed cells. Nevertheless, neither phagotrophy nor
uptake of re-leased DOM did seem to boost the growth rate of P.
parvum . However, the prey was lysed, before the P. parvum got
nutrient limited in any of the treatments in the present study, and our
data supports the idea that phagotrophy in P. parvum may be a
strategy to compensate for nutrient limitation. Our findings indicate
that low salinity is the main factor that induces higher degree of prey
lysis, while P starvation seem to induce higher phagotrophy rates inP. parvum .
Phagotrophy involves the internalization of food via endocytosis and the
subsequent formation of a phagosome, which fuses with lysosomes for
further digestion. In mixotrophic Alexandrium , expression of
endocytosis genes was more enhanced in a lytic strain as compared to a
non-lytic strain, highlighting the potential coupling be-tween the
processes of lytic toxin production and phagotrophy (Wohlrab et
al. , 2016). In the current study, gene expression associated with
phagotrophy-related processes were induced by both salinity and P
depletion, indicating that mixotrophy is induced in P. parvumunder stress conditions. Genes involved in endocytosis were consistently
up-regulated under low salinity and P starvation, with both treatments
inducing strong prey lysis/mortality and feeding in P. parvum .
Expression of phagotrophy-related genes has been previously related to
ingestion rates in mixotrophic flagellates (McKie-Krisberg et
al. , 2018). Moreover, factors that influence the expression of such
genes include prey availability and light (Lie et al. , 2017). Our
incubation experiments showed higher phagotrophy under P depletion
independent of salinity. However, potential phagotrophy and/or DOM
uptake might have been underestimated, due to higher excretion of toxins
at low salinity, which could cause prey lyses.
Polyketide synthases
Polyketide synthase genes are secondary metabolites that have been
extensive studied in marine protists (John et al. , 2008; Monroe
and Dolah, 2008; Kohli et al. , 2016). Many phycotoxins are
polyketides suggest that PKSs are involved in toxin biosynthesis.
Prymnesins can have carbon backbone lengths, from 83 to 91 C (Binzeret al. , 2019). The considerable carbon length of toxins
highlights the complexity of the underlying molecular biosynthetic
mechanisms. Their biosynthesis could potentially involve both PKSs and
perhaps partly fatty acid synthases, as has previously been suggested
for the biosynthesis of antibiotics from bacteria (Masschelein et
al. , 2013). Light-dark dependent expression of PKS has been previously
studied in synchronized cultures of the ichthyotoxic haptophytePrymnesium polylepis , which led to the identification of 13
potential PKS sequences (John et al. , 2010). In P. parvum ,
physiological treatments such as high irradiance and low salinity shock
have been shown to induce higher copy numbers of PKS (Freitag et
al. , 2011). Polyketide synthase genes have previously been reported inP. parvum strains that produce different types of prymnesins
(Anestis et al. , 2021), however, the development of efficient
genetic manipulation techniques would be required for better
understanding of the connection between gene and product. In the current
study, the expression of PKSs was strongly influenced by cell density,
coinciding with higher cellular content of prymnesins. The expression
patterns highlight the presence of PKS gene clusters, which were,
interestingly, higher expressed under P depletion. Under these
treatments, phagotrophy was also higher, thus argue for the potential
involvement of their product in prey capture or lysis. These finding
certainly need further investigation.
Implications for bloom maintenance
Maintaining high cell concentrations over weeks during algal blooms
challenges cellular and metabolic performances of algal cells as
nutrients become limiting. Our findings suggest rearrangements of carbon
metabolism and down-regulation of energy anabolism, with cellular
transcription and translation, being considerably inhibited during P
depletion. However, even under P depletion the expression of polyketide
synthases was high and increased at high cell densities and under P
depletion. Assuming that polyketide synthases are indeed the encoding
genes for prymnesins and given the high amount of intracellular
prymnesin, this would imply that cells under P depletion invest
substantial amounts of carbon units and energy in the production of
these energetically expensive secondary metabolites. The benefit of such
an investment could be higher competitive abilities via prey capture,
lyses and/or increased feeding. Such a response would be evolutionary
advantageous when prey is available, and the production and release of
lytic toxins could contribute to increased nutrient availability and/or
direct prey uptake by P. parvum . The additional up-regulation of
endocytic genes under P depletion and low salinity could suggest the
preparation of the molecular toolkit for phagocytosis when nutrients
become the limiting factor. Such a response would allow the further
domination of P. parvum under bloom condition and the engagement
in alternative nutrition modes for the maintenance of its population.
Conclusions
Salinity, phosphorus availability and cell density had important impact
on different aspects of P. parvum physiology. Prymnesin contents
were significantly higher in high cell density cultures, while salinity
and P availability influenced the composition of prymnesin analogues.
Gene expression of metabolic genes was in accordance with the observed
growth rates, with up-regulation of catabolic genes under high growth
rates. Prey lysis was faster at low salinity, while P starvation induced
higher phago-trophic rates. Phagotrophy did not increase cell growth,
supporting the idea that mixotrophy in P. parvum may be a
survival strategy to cope with nutrient limitation, particularly
expected during bloom conditions. The gene expression data supports the
increased potential for mixotrophy under low salinity and P-starvation
conditions, with up-regulation of endocytosis related genes. The
expression of PKSs was generally higher at high cellular toxin content
condition, and especially at P depleted cells, which were characterized
by increased phagotrophy.
AUTHOR CONTRIBUTIONS
KA and UJ designed the study, KA performed the experiments, KA, SW, EV
and UJ analyzed and interpreted the data, UJ supervised the study. All
authors contributed to drafting the manuscript.
ACKNOWLEDGEMENTS
This work has been funded by European Union’s Horizon 2020 research and
innovation programme under grant agreement No. 766327. UJ and SW were
financially supported under the POF IV Topic 6 ST 6.2 of the Alfred
Wegener Institute, Helmholtz Centre for Polar and Marine Research,
Germany and the Helmholtz Institute for Functional Marine Biodiversity.
EV received funding of the Austrian Science Fund (FWF) through an
Erwin-Schrödinger fellowship [J3895-N28] and by the University of
Vienna.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
DATA AVAILABILITY STATEMENT
The raw read sequences and transcriptome have been deposited at the
National Center for Biotechnology Information under the BioProject
PRJNA718746. The data for the physiological parameters is provided at
the Appendix.
TABLE AND FIGURE LEGENDS
Table 1 | Regulation of the expression of catabolic
and anabolic genes in Prymnesium parvum as fold-change in the
comparison between low salinity and high salinity.
Table 2 | Contigs encoding for highly expressed
polyketide synthases in Prymnesium parvum (clusters D and I of
Figure 6), their length in base pairs and their corresponding functional
domain organization.
Figure 1 | Overview of sample parametersPrymnesium parvum for different cell densities and treatments (HS
= high salinity, LS = low salinity, HP = high phosphorus and LP = low
phosphorus). Cell growth (a) and indicated with arrows are the sampling
time points for low cell density (LD) and high cell density (HD).
Further parameters include phosphate concentration (b); particulate
organic carbon (c); particulate organic nitrogen (d); carbon:nitrogen
ratio (e); chlorophyll-a concentration (f).
Figure 2 | Total cellular prymnesin content inPrymnesium parvum (attomol cell-1) (a) and
percentage prymnesin analog composition (b) for all treatments (HS =
high salinity, LS = low salinity, HP = high phosphorus and LP = low
phosphorus) and cell densities (LD = low density and HD = high density).
Concentration of Teleaulax acuta (cells mL-1),
when incubated with Prymnesium parvum (c), and percentage ofP. parvum cells containing a food vacuole (d).
Figure 3 | Overview of statistics for the generated
transcriptome of Prymnesium parvum (a), Principal Components
Analysis (PCA) of the transcriptomes for the samples and their
corresponding cell densities and conditions (b), and number of
transcripts for which salinity (Sal), phosphorus availability (P), cell
density (CD) and all combinatory interactions had a statistically
significant (adjusted p < 0.01) effect on their expression
(c).
Figure 4 | Number of up- and down-regulated genes inPrymnesium parvum , assigned per KEGG category for cellular
processes (orange), environmental information processing (green),
genetic information processing (blue) and metabolism (brown). The
comparisons include (a) low phosphorus (LP) vs high phosphorus (LP), (b)
low salinity (LS) vs high salinity (HS) and (c) low cell density (LD) vs
high cell density (HD).
Figure 5 | Expression level of differentially
expressed genes involved in transport and catabolism in Prymnesium
parvum . The categories include genes involved in endocytosis,
phagosome, lysosome and peroxisome. The heatmap shows the expression
levels across different cell densities (low and high) and for all
treatments (HS = high salinity, LS = low salinity, +P = high phosphorus
and -P = low phosphorus).
Figure 6 | Expression level of polyketide synthase
genes in Prymnesium parvum . The heatmap shows the expression
value as transcripts per million (TPM) across different cell densities
(low and high) and for all treatments (HS = high salinity, LS = low
salinity, +P = high phosphorus and -P = low phosphorus). Hierarchical
clustering was performed based on the expression profile and lead to the
formation of 10 clusters (A-J).