Introduction
Proteins and carbohydrates constitute two of the most common labile organic
substrates in the ocean (Benner, 2002; Benner et al., 1992; McCarthy et al., 1996), both of which are essential for cellular
growth and repair (Azam et al., 1983; Simon and Azam,
1989). Labile substrate availability is limited by bacterial enzyme-driven
hydrolysis of high molecular weight organic material (Azam and Cho, 1987;
Münster, 1991). Two groups of bacterial extracellular enzymes (attached or
released into surrounding water) commonly studied for their role in protein
and carbohydrate degradation are aminopeptidases and glucosidases
respectively. The activity of individual enzymes is responsive to changes
in environmental factors, and so overall glucosidase and peptidase
activities will have different pH optima (Tipton and Dixon,
1979; Piontek et al., 2013). Consequently a change in ocean pH may result in
a decline or increase in activity of extracellular enzymes as these are
directly exposed to the external seawater pH (Orsi and
Tipton, 1979; Tipton and Dixon, 1979).
Atmospheric CO2 has increased by 40 % since the 18th century
(IGBP-IOC-SCOR, 2013; IPCC, 2013), which is of
concern as CO2 freely exchanges with the ocean and directly alters
ocean carbonate chemistry and pH. As a result ocean pH has declined from 8.2
to 8.1, with a continued decline to 7.8 predicted by the year 2100. This
decline in ocean pH and the associated change in carbonate chemistry,
referred to as ocean acidification (OA), will significantly impact metabolic
reactions and influence carbon cycling in the ocean
(Endo et al., 2013; Engel et al.,
2014; Piontek et al., 2010; Riebesell et al., 2007). For this reason,
researchers have investigated the sensitivity of a wide range of biotic and
abiotic factors to future changes in ocean pH and the carbonate system.
Bacterial extracellular enzyme activity has been investigated in OA studies
(reviewed in Cunha et al., 2010) due to the important role
they play in the degradation of organic matter (Azam
and Ammerman, 1984; Azam and Cho, 1987; Law, 1980; Münster, 1991) and
the vertical flux of carbon to the deep ocean
(Piontek et al., 2010; Riebesell and Tortell, 2011;
Segschneider and Bendtsen, 2013). Current research suggests that bacterial
extracellular enzyme activities may increase under future OA conditions
(Grossart et al., 2006; Maas et al.,
2013; Piontek et al., 2010, 2013; Yague and Estevez, 1988). This may result
from the direct effect of pH on the ionisation state of the enzyme's
component amino acids (Dixon, 1953) or from indirect influences
potentially altering enzyme production (Boominadhan et al., 2009). Examples
of the latter include changes in the concentration and composition of high
molecular weight organic substrate due to the effect of pH on phytoplankton
and bacterioplankton community composition
(Endo et al., 2013; Engel et al., 2008; Riebesell, 2004; Witt et al., 2011), bacterial secondary
production (BSP) and cell numbers (Endres et al., 2014; Maas et al., 2013), and
phytoplankton-derived organic exudation (Engel, 2002;
Engel et al., 2014).
Bacterial extracellular enzyme activity is regularly determined using
artificial fluorogenic substrates. These substrates consist of a fluorescent
moiety covalently linked to one or more natural monomer molecules
(Arnosti, 2011; Kim and Hoppe, 1984). The molecule is
non-fluorescent until it is hydrolysed by an extracellular enzyme, which
triggers a fluorescent response, allowing it to be detected and quantified
(Hoppe, 1993). The sensitivity of the analytical method to pH
has been assessed in terrestrial soils
(Malcolm, 1983; Niemi and Vepsäläinen, 2005); however, limited information is
available on how these components respond to a reduction in seawater pH
(Piontek et al., 2013). If pH does have a significant effect on the
individual assay components, and this is not corrected, then calculated
enzyme kinetics will under- or overestimate the true activity rates.
Several different methods have been used to artificially adjust seawater pH
in experimental systems (Cornwall and Hurd, 2015; reviewed
in Riebesell et al., 2010). The simplest acidification method involves the
addition of a strong acid (typically HCl). The acid decreases the sample pH
through the formation of hydronium ions and modifies total alkalinity (TA)
but does not alter dissolved inorganic carbon (DIC) in a closed system
(Emerson and Hedges, 2008); consequently, although it is
relatively simple to adjust pH using acid, the balance of carbonate species
does not reflect the changes that will occur in response to increased
CO2 uptake unless corrected for by the addition of a base
(Iglesias-Rodriguez et al., 2008; Riebesell et al.,
2010). Another method for acidifying seawater is the use of CO2–air gas
mixtures, which alter the seawater carbonate species in ratios predicted to
occur from the uptake of atmospheric CO2 under future scenarios
(Gattuso and Lavigne, 2009; Riebesell et al., 2010; Rost et al., 2008; Schulz et al.,
2009). Schulz et al. (2009) suggest that microbial
organisms are likely to respond to changes in carbonate species (e.g.
CO2, HCO3-, or CO32-) rather than changes in
overall DIC or TA. A review by Hurd et al. (2009) concluded that differences in carbonate chemistry arising from the
use of different acidification methodologies can influence phytoplankton
photosynthesis and growth rates, as well as particulate organic carbon
production per cell, and so it is important to ensure changes in all
carbonate system species reflect that projected from an increase in CO2
(Cornwall and Hurd, 2015).
In addition to the method of acidification, the mode of application also
needs to be considered. A commonly used method of introducing CO2–air
gas mixtures into seawater is by bubbling. This method is simple to
implement and maintain for extended periods; however, the physical
disturbance associated with bubbling CO2 gas may influence coagulation
of organic matter (Engel et al., 2004; Kepkay and
Johnson, 1989; Mopper et al., 1995; Passow, 2012; Schuster and Herndl, 1995;
Zhou et al., 1998), as well as microbial interactions (Kepkay
and Johnson, 1989). This mechanical disturbance may be particularly
exacerbated when bubbling is used in small-volume incubations at the
laboratory/microcosm experimental scale (< 20 L). An
alternative method of introducing CO2 gas is by using gas-permeable
tubing (Law et al., 2012; Hoffmann et al.,
2013), which eliminates physical artefacts associated with bubbling whilst
achieving realistic future carbonate chemistry. Previous research has been conducted
comparing the effect of acid addition and CO2 gas bubbling on
phytoplankton growth, with no significant difference detected
(Chen and Durbin, 1994; Hoppe et al., 2011;
Shi et al., 2009). However, to date no comparison of the bacterial response
to seawater acidified with acid and CO2 gas aeration has been carried
out. In addition, there are no published comparisons of CO2 gas
mixtures introduced through gas-permeable silicon tubing with bubbling to
assess their suitability for OA research. Consequently the aims of the
following study were two-fold: to identify any artefacts associated with the
use of fluorogenic substrates in extracellular enzyme analysis and also to
compare the response of bacterial processes to different methods of
acidification in small-volume incubations.
Material and methods
pH determination
Sample pH was determined using a CX-505 laboratory multifunction meter
(Elmetron) equipped with a platinum temperature integrated pH electrode
(IJ44C-HT enhanced series; accuracy 0.002 pH units), calibrated using Tris
buffers (Cornwall and Hurd, 2015), and regularly cleaned using potassium
chloride reference electrolyte gel (Ionode RE45). Electrode pH measurements
were validated using a pH spectrophotometer with colorimetric determination
using a thymol blue dye solution (Law et al.,
2012; McGraw et al., 2010). Following recommendations in the European
Project on Ocean Acidification (Riebesell et al., 2010), pH
values of this research reflect the total hydrogen ion scale (pHT).
Extracellular enzyme activity
The activity of two proteases was examined, with arginine aminopeptidase
activity (AAP) quantified using L-arginine-7-amido-4-methylcoumarin
hydrochloride (Arg-MCA) and leucine aminopeptidase activity (LAP)
quantified using L-leucine-7-amido-4-methylcoumarin hydrochloride (Leu-MCA).
Two glucosidases were also examined: α-glucosidase activity (AG) was
quantified using 4-Methylumbelliferyl a-D-glucopyranoside (α-MUF),
and β-glucosidase activity (BG) was quantified using
4-Methylumbelliferyl β-D-glucopyranoside (β-MUF, all from
P212121 LLC, USA). Artificial fluorogenic substrate was added to each
seawater sample to give a final substrate assay concentration of 39 µM,
which was determined from independent tests to be the optimum
concentration for calculating the maximum velocity of enzyme hydrolysis in
seawater samples (data not shown). A four-point calibration curve (0, 4, 40,
200 nM final concentration) was created at both pH 7.8 and 8.1 using
4-Methylumbelliferone (MUF) for glucosidase activity, with a separate
calibration curve (0, 40, 400, 4000 nM final concentration) created using
7-amino-4-methylcoumarin (MCA) for protease activity (Sigma-Aldrich).
Ultra-pure distilled water (Invitrogen™, Life Technologies) was used as
a sample blank. Each sample was assayed in triplicate using a single
96-microwell flat bottom black assay plate (Nunc A/S), with a separate
enzyme assay performed for glucosidase and protease activity. Each assay
plate was read at 5 min intervals for a minimum of 3 h using a Modulus
microplate reader (Turner Biosystems) at 365 nm excitation and 460 nm
emission wavelength as in Burrell et al. (2015). Incubation assay
temperature matched the seawater temperature at the sampling site. The
potential for outgassing and associated increase in sample pH during the 3 h
enzyme assay was not tested. The maximum potential enzyme rate (Vmax,
nmol L-1 h-1) was approximated from the saturating substrate
concentration of 39 µM. Triplicate Vmax approximations were
averaged per sample. Cell-specific rates were calculated by dividing the
activity per litre by bacterial cell numbers per litre. The assay tests were
carried out using surface seawater collected from the southern coast of
Wellington, New Zealand (41∘20′53.0′′ S, 174∘45′54.0′′ E).
Enzyme assays
The effect of pH on fluorophore fluorescence
The effect of pH on fluorophore fluorescence was investigated at both
typical (Hoppe, 1983) and elevated fluorophore concentrations using two
different buffer solutions, the organic solvent 2-methoxyethanol
(Sigma-Aldrich)
and 0.1 M Tris/HCl. The pH of MUF and MCA fluorophore
working standard (200 µM) diluted in 1 % 2-methoxyethanol
(Sigma-Aldrich) was first recorded (pH 6.22 and 6.58 at 18.6 ∘C
respectively). Each fluorophore was then diluted to 4000, 20 000, and 40 000 nM
(referred to as high concentrations) at four pH values (8.2, 8.1, 7.9, and
7.8) in triplicate by addition of 0.1 N aqueous NaOH. The MUF and MCA
fluorophore working standards made up in 0.1 M Tris/HCl were prepared at pH
8.1 and 7.8 only and also carried out at lower concentrations (MUF: 4, 40,
200 nM; MCA: 40, 400, 4000 nM).
The effect of artificial fluorogenic substrate on seawater pH
Individual seawater samples were adjusted to pH 7.95 and 7.70 using 0.1 M HCl.
All four artificial fluorogenic substrates previously described were
made up to working standards using 1 % 2-methoxyethanol (Sigma-Aldrich).
A time-zero reference pH was recorded for each seawater sample and,
following the addition of each substrate at 39 µM final
concentration, sample pH was recorded immediately and after 30 min. Each
artificial fluorogenic substrate was run in triplicate at both pH values
and compared to controls without substrate addition at both pH levels.
Buffering artificial substrates
Duplicate trials were undertaken to determine if 0.1 M Tris/HCl could
successfully buffer MCA substrate at the working concentration (39 µM)
when added to seawater of similar pH. Tris buffer contains an amine group
which can affect peptidase activity (Baker and Prescott, 1983; Desmarais et
al., 2002; Saishin et al., 2010), and so tests were carried out to compare
the impact of different buffers. LAP activity was compared in seawater using
LAP substrate (39 µM final concentration) buffered with 0.1 M
Tris/HCl or 3-(N-morpholino)propanesulfonic acid (MOPS) with pH adjusted to
8.1. Enzyme activity was also determined in seawater (pH 8.18). A
non-buffered LAP substrate addition was not included due to the acidic
nature of the aminopeptidase substrate (non-buffered LAP substrate was pH
5.87). MOPS has been used as a buffer in studies of the effects of pH on
enzymes (Piontek et al., 2010) and so was an appropriate comparison. Borate
buffers were not trialled because they have a bactericidal effect on
microbial activity (Houlsby et al., 1986). In two separate
test experiments using coastal seawater Tris/HCl buffer did not inhibit LAP
activity relative to MOPS but instead showed a minor stimulatory effect with
16–18 % higher LAP activity (Supplement Table S1). Tris/HCl was
selected for subsequent use as its optimal buffer range is pH 7.8–9.0,
making it ideal for OA incubations, and it has a pKa of 8.06 and so is
appropriate for artificial fluorescent substrates (Hoppe, 1993).
Based on the buffer trials, the following methodology was used for the
seawater acidification tests. Tris-buffered Leu-MCA and Arg-MCA substrate
working standards were made by diluting 500 µL of MCA substrate stock
(16 mM) with 4.5 mL of 0.1 M Tris/HCl buffer. Duplicate Tris/MCA substrate
solutions were adjusted to pH 8.1 and 7.8 by adding 10 % HCl and the pH
of duplicate 10 mL aliquots of coastal seawater was also adjusted to pH 8.1
and 7.8. For each pH treatment, 250 µL of Tris/MCA substrate solution
was added to 10 mL of seawater fixed at the corresponding pH. pH was
recorded at room temperature using a pH electrode as described above.
Seawater acidification approach
The influence of acidification technique on biotic parameters was
investigated in two separate experiments conducted under controlled
temperature conditions in late summer (May 2013 – trial 1) and in early
spring (October 2013 – trial 2). Coastal seawater was first filtered through
a 15 µm filter and then a 1 µm inline cartridge filter. Three
different methods were used to acidify seawater to that predicted by the end
of the century (pH 7.80) (IPCC, 2013): (A) acid addition using 0.1 M HCl,
(B) bubbling CO2–air gas mixture through an acid-washed aquarium
airstone, and (P) CO2–air gas mixture introduced through gas-permeable
silicon tubing (Tygon Tubing R-3603; ID 1.6 mm, OD 3.2 mm; Law et al., 2012).
Treatment P was acidified to a pH of 7.8 by the sequential application of
100 % synthetically produced CO2 gas for 25 min, followed by 10 %
CO2 gas (in 20.8 % O2 in N2; BOC Gas Ltd) for 60 min at a
flow rate of < 26 mL min-1. The initial use of pure and 10 %
CO2 gas made it possible to reach the target pH within 3 h. Treatment B
was acidified by bubbling seawater with 742 µatm CO2 gas (in
20.95 % O2 in N2; BOC Gas Ltd) for 143 min at
< 25 mL min-1 to achieve the target pH 7.80. The volume of 0.1 M HCl required
to acidify treatment A to pH 7.8 (2.0 mL – trial 1; 3.1 mL – trial 2)
was calculated based on the sample volume, DIC and alkalinity (K. Currie, NIWA/University of Otago, personal
communication, 2013) using an algorithm from
Dickson et al. (2007). To ensure a consistent rate of pH
change across treatments, treatment B and A were adjusted to match that of
the slower treatment P (150 min), with the pH of each sample verified using
a pH electrode. Each treatment and an ambient seawater control were then
incubated in triplicate in acid-washed milli-Q water-rinsed 4.3 L
low-density polyethylene (LDPE) cubitainers (Thermo Fisher Scientific),
without a headspace. pH was monitored throughout each 96 h incubation
(Supplement Figs. S2 and S3), however no further pH adjustment took
place.
Each cubitainer was housed in one of two identical perspex incubation
chambers (1730 mm long, 450 mm high by 325 mm deep), set at in situ ambient
seawater temperature (15.1 ∘C – trial 1; 15.5 ∘C –
trial 2). Artificial light (700–900 µE m-2 s-1) was
maintained in each cubitainer through external fluorescent light banks
(Philips TLD 36 W/840); neutral density polycarbonate screening ensured
light intensities were uniform between incubation chambers, while adjustable
timers ensured an automated diurnal 12 h light/dark cycle. Mixing of water
in each cubitainer was achieved using an inflating diaphragm positioned
underneath each cubitainer, with the inflation and collapse of the diaphragm
under the weight of the sample resulting in continual water mixing.
Cubitainers were also manually removed and inverted three times prior to
each sampling. Time-zero sampling occurred after initial pH adjustment.
Assay fluorophore and substrate standard solutions were adjusted to
treatment pH.
Cell-specific extracellular enzyme activity (mean ± SE,
n= 3) in response to seawater acidified with 0.1 M HCl (A), bubbled with
CO2–air gas mixture (B) and CO2–air gas mixture introduced through
gas-permeable silicon tubing (P). (a) BG activity in trial 1; (b) BG
activity in trial 2; (c) LAP activity in trial 1; (d) LAP activity in trial
2.
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Bacteria and picoplankton cell numbers
Triplicate samples were collected in 2 mL Cryovials (Raylab Ltd) and frozen
in liquid nitrogen (Hall et al., 2004) for up to 12 weeks
prior to analysis. Bacterial cell numbers were determined by flow cytometry
(FACSCalibur, Becton-Dickinson) following staining with SybrGreenII
(Invitrogen) (Lebaron et al., 1998), and count
events were normalised to volume using TruCount bead solution (BD
Biosciences) (Button and Robertson, 1993). Total eukaryotic
picoplankton numbers (< 2 µm) were determined by fluorescence
of chlorophyll (wavelength 670 nm), phycoerythrin (585 nm), and
phycourobilin (530 nm) as well as forward light scatter providing an
estimate of cell size. Final count values were recorded as cells mL-1.
Bacterial secondary production
Potential BSP was measured using
3H-leucine (3H-Leu) of high specific activity (> 80 Ci mmol-1,
SciMed Ltd) in triplicate 1.7 mL samples. Following the TCA
precipitation and centrifugation methodology (Kirchman,
2001; Smith and Azam, 1992), 3H-Leu incorporation was determined using
a liquid scintillation counter (Tri-Carb 2910 TR) and converted to secondary
production using a protein conversion factor (1.5 kg C mol-1 leucine)
(Simon and Azam, 1989). Cell-specific rates were calculated by
dividing the BSP rate by total bacterial cell numbers.
Dissolved inorganic carbon and total alkalinity
Pre-combusted 12 mL sample DIC vials (Labco Ltd) were triple rinsed with
sample seawater and filled, ensuring no air bubbles. One drop of saturated
HgCl2 was added to each DIC sample, with storage at room temperature.
DIC was determined using evolved CO2 gas after sample acidification on
a Marianda AIRICA system, the accuracy of this method was estimated to be
±5 µmol kg-1, as determined by analysis of certified
reference material. Alkalinity samples were collected by filling a 1 L
screw top bottle, following the same sample preparation and storage
procedures as DIC above. Samples were later analysed by potentiometric
titration in a closed cell (Dickson et al., 2007) with an
accuracy of ±2 µmol kg-1, also determined by analysis of
certified reference material.
Statistical analysis
Statistica v.10 (StatSoft Inc., USA) was used for basic graphics and
descriptive statistics. Data were tested for normality and equality of
variance prior to statistical analysis. Data were log(x+1) transformed due
to the small sample size at each sampling point. Standard hypothesis
formulations were used for each analysis of variance (ANOVA); the null
hypothesis (H0) was μ= 0. The significance level of each test
was p≤ 0.05. If H0 was rejected, a Tukey's HSD post hoc analysis
test was run to identify individual variable responses.
Results and discussion
Enzyme assay methodology
MUF and MCA fluorescence was lower at pH 7.8 relative to pH 8.1, as
previously reported in soils
(Niemi and Vepsäläinen, 2005). The fluorescence of the unbuffered MUF
2-methoxyethanol at 40 000 nM was 20 % higher at pH 8.1 than at pH 7.8
(t test, p < 0.05), while MUF Tris-buffered fluorescence at 200 nM was
3.2 % higher at pH 8.1 (t test, p > 0.05; Table 1). MCA 2-methoxyethanol
fluorescence at 40 000 nM was 25 % higher at pH 8.1 than fluorescence at pH
7.8 (t test, p < 0.05), while MCA Tris-buffered fluorescence at 200 nM was
1.7 % higher at pH 8.1 than at pH 7.8 (t test, p > 0.05; Table 1). Due to the
basicity of the MCA amino group, fluorescence intensity is less affected by
pH and it has been suggested that buffering is not required in seawater
(Piontek et al., 2013; Endres et al., 2014), whereas buffering of MUF has
been reported (Piontek et al., 2010, 2013; Endres et al., 2013). Our results
confirm that pH has a significant effect on unbuffered MUF and MCA
fluorescence and that 0.1 M Tris buffer minimises any pH effect at typical
working concentration.
Bacterial cell numbers (mean ± SE, n= 3) in response to
seawater acidified with 0.1 M HCl (A), bubbled with CO2–air gas mixture
(B) and CO2–air gas mixture introduced through gas-permeable silicon
tubing (P). (a) Trial 1. (b) Trial 2.
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Cell-specific bacterial secondary production (mean ± SE,
n= 3) in response to seawater acidified with 0.1 M HCl (A), bubbled with
CO2–air gas mixture (B) and CO2–air gas mixture introduced through
gas-permeable silicon tubing (P). (a) Trial 1. (b) Trial 2.
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Mean fluorophore fluorescence at pH 8.1 ad 7.8 (RFU, n= 3, ±SD).
Concentration
Fluorophore
pH 8.1
pH 7.8
(nM)
0.1M Tris
200
MUF
1604.24 (±17.86)
1553.18 (±38.41)
MCA
13653.69 (±1518.05)
13420.72 (±2005.05)
Although there is awareness of the effect of pH on fluorophore fluorescence
(Mead et al., 1955; Piontek et al., 2013; Endres et al., 2014), few studies
consider the effect of fluorescent substrate addition on seawater pH.
Immediately following the addition of non-buffered Leu-MCA or Arg-MCA
substrate to seawater at pH 7.95 or 7.70, pH decreased by at least 0.05
units for each substrate and remained significantly lower 30 min after
addition when compared to time-zero pH (one-way ANOVA, p < 0.05). As
both MCA substrates are hydrochloride salts, addition resulted in a
significant pH change, as previously reported by Hoppe (1993). In tests
adding Tris-buffered MCA substrate solutions adjusted to pH
7.8 and 8.1 to seawater at the same pH, the resulting pH change ranged from
0.003 to 0.03 units (±0.001 SE). As the addition of buffer solution
minimised the pH change, both MCA substrates and fluorophores were
subsequently produced using 0.1 M Tris/HCl, with pH adjusted to that of the
respective experimental treatments and control. In contrast to MCA, no
statistically significant change in pH was recorded immediately following,
or 30 min after, the addition of either α-MUF or β-MUF substrate
to seawater at pH 7.95 or 7.70, indicating that these are neutral compounds.
However, to eliminate possible bias, MUF substrates were also buffered using
Tris.
Seawater acidification
Having established that the analytical procedures for determining
extracellular enzyme activity are affected by, and alter, pH, the influence
of acidification technique was then considered in two separate trials in
different seasons. Overall, the experiments showed that different
acidification techniques had significant effects on BG and LAP activity at
select time points in both trials (Fig. 1), while the response of AG and AAP
activity was variable with no consistent treatment response relative to the
control (Figs. S4, S5, and S6). Overall, BG and AG activity
declined from time-zero to 96 h in the control and treatments in trial 1
but were both significantly higher in the treatments relative to the control
from time-zero to 72 h, with BG activity approximately 3-fold higher
than AG activity (data not shown). Cell-specific BG activity was at least an
order of magnitude higher in treatments B, P, and A relative to the control at
time-zero (one-way ANOVA, p < 0.05) (Fig. 2), which is consistent with
a direct effect of acidification (Piontek et al., 2013). Cell-specific BG
activity was highest in treatment B from 24 to 72 h by at least 14 %
relative to treatment A and P (Fig. 1). In contrast to trial 1,
cell-specific BG activity increased significantly throughout trial 2
(repeated measures ANOVA, p < 0.05). The opposing temporal trends
between trials may signify seasonal differences in the response of
glucosidase to OA, potentially reflecting differences in microbial community
composition (Endo et al., 2013) or substrate availability (Morris and
Foster, 1971). There was no significant difference in BG activity between
treatments at time-zero in trial 2 (one-way ANOVA, p > 0.05)
(Fig. 2), and BG activity was again highest in treatment B from 48 h, with
activity at least 18 % higher relative to treatments P and A (Fig. 1).
Bulk water LAP and AAP activity varied between treatments for trials 1 and
2. For example, both LAP and AAP activity were highest in treatment P
throughout trial 1, whereas LAP activity was highest in treatment B from 72
to 96 h in trial 2 (data not shown). Although cell-specific LAP activity
showed evidence of a response to acidification at select time points, there
was no consistent significant response throughout either trial (Fig. 1).
Although treatment B was only bubbled with gas mixtures for the
pre-incubation period (143 min), this had a greater effect on BG activity
than in the other treatments, indicating potential artefacts associated with
bubbling. Bubbling may have ruptured picoplankton cells or increased their
susceptibility to viral lysis, leading to an increase in the release of
labile organic carbohydrates. This is potentially supported by the decline
in total eukaryotic picoplankton cell numbers in treatment B (trial 1 – 2.8 × 103
to 2.6 × 103 cells mL-1, trial 2 – 1.7 × 103 to
1.3 × 103 cells mL-1) in both trials (repeated measures ANOVA,
p < 0.01). An increase in enzyme activity would theoretically increase the
availability of low molecular weight organic substrate for bacterial
assimilation and may explain the significant increase in bacterial cell
numbers in treatment B relative to the control at 96 h in both trials
(one-way ANOVA, p < 0.05) (Fig. 2). An increase in bacterial abundance
in response to bubbling has been previously reported by
Kepkay and Johnson (1989), who suggested that surface DOC
coagulation facilitated by bubbling resulted in increased respiration and
bacterial numbers. It is possible that bubbling increased the abiotic
coagulation of organic matter (Riley, 1963) and formation of high
molecular weight substrate such as transparent exopolymer particles (Mopper
et al., 1995; Passow, 2012; Schuster and Herndl, 1995; Zhou et al., 1998),
which could explain the elevated cell-specific BG activity (Fig. 1).
All acidification treatments had a significant negative effect on
cell-specific BSP from 24 to 48 h in trial 1 (one-way ANOVA, p < 0.05)
(Fig. 3). During trial 2, cell-specific BSP was significantly lower in
treatments B and P when compared to the control from 72 to 96 h (one-way
ANOVA, p < 0.05), while BSP was twice as high in treatment A during
this period (Fig. 3). Although a clear treatment response was not observed
in either trial, the low cell-specific BSP in treatment B relative to the
control and treatment A at 96 h in trial 2 was surprising as enzyme activity
and bacterial cell numbers were elevated. Existing literature also reports
variable BSP responses to acidified conditions. Arnosti et al. (2011) and
Teira et al. (2012) detected no significant BSP response, while Grossart et
al. (2006) detected an increase, and Maas et al. (2013) and
Siu et al. (2014) recorded a decrease in
BSP rates with increasing CO2. As the same response was not observed in
trial 1, it is possible that additional indirect factors such as bacterial
community composition or substrate type may have influenced BSP under OA
conditions (Piontek et al., 2013).
Conclusions
Artificial fluorogenic substrates have been used to investigate bacterial
extracellular enzyme activities in aquatic environments for decades (Hoppe,
1983; Somville and Billen, 1983). Although the technique has several
limitations, including that the artificial fluorogenic substrate may not
represent the naturally occurring substrate (Chróst, 1989) so that the
observed activity only represents potential hydrolysis (Arnosti, 1996;
Unanue et al., 1999), the technique is rapid and easily applied in the field
and most importantly, allows for a standardised method for comparison of
results in different OA studies. This study confirmed that specific
artificial fluorogenic substrates used to determine extracellular enzyme
activity can alter sample pH and, consequently, that buffering is required,
particularly when used in OA research. Seawater acidification stimulated
β-glucosidase activity as previously reported (Piontek et al., 2010;
Burrell et al., 2015), but the use of different methodological approaches
may generate variable results. Acid addition does not produce realistic
seawater carbonate chemistry predicted in a future ocean
(Riebesell et al., 2010), and bubbling with CO2 gas has
a significant effect on β-glucosidase activity and bacterial cell
numbers, indicating artefacts associated with bubbling. It should be noted
that these effects were observed in small-volume laboratory-scale
experiments (< 10 L) and may have less impact in larger-scale
experiments. Although not all techniques previously used to artificially
adjust seawater pH were trialled (Riebesell et al., 2010), the results
presented here indicate that introducing CO2–air gas mixtures using gas-permeable silicon tubing is an effective technique for investigating the
response of bacterial processes to future OA conditions, and it appears
superior to alternatives methods. This approach should be considered for
broader use in standardised protocols for ocean acidification (Riebesell et
al., 2010; Cornwall and Hurd, 2015) to achieve robust meta-analyses and
international intercomparisons.