DOI: 10.5061/dryad.44j0zpcr4
title: Salinity-temperature interaction drives metabolic and energetic changes in an Arctic crustacean

description: The Arctic is shifting towards a prevalence of warm and more saline
 Atlantic-like waters. These changes in the marine environment pose
 significant challenges for the eco-physiology of marine invertebrates.
 Here we measured the metabolic enzyme activity of citrate synthase and
 lactate dehydrogenase, as well as the energy content and level of
 oxidative damage in 71 individuals (~ 10/station) of Thysanoessa inermis
 collected in six fjords in Svalbard that were characterized by different
 levels of influence of Atlantic water and, thus, temperature and salinity
 variability in the water column. T. inermis inhabiting fjords with strong
 influence of Atlantic water masses had lower lipid and protein content,
 and higher anaerobic metabolism compared to those from more Arctic fjord
 types. Moreover, T. inermis collected in fjords with high variability in
 both temperature and salinity had 0.8-fold lower lipid content than
 station with more stable temperature and salinity. Our results suggest
 that T. inermis in fjords influenced by Atlantic waters is possibly under
 stress leading to increased metabolism, consequently enhancing energy
 consumption. If the energy consumption is not compensated for, by an
 uptake, it could result in a decrease of total biomass of T. inermis with
 possible consequences for the entire Arctic food web.
description: <em>Sampling</em> At each station,
 measurements of temperature, salinity and fluorescence were obtained by a
 ship-board conductivity, temperature, and depth (CTD) profiler
 (SBE911plus, SeaBird Electronics) with a SeaPoint fluorometer attached.
 The latitude and longitude of sampling locations are given in Table 1 as
 well as the average temperature and salinity of the sampling location from
 the bottom to 5m depth. We have also calculated the variation (i.e., delta
 = maximum value minus minimum value recorded) of both salinity and
 temperature from the bottom to 5 m depth to estimate how much variation in
 these variables euphausiids will encounter during their diel vertical
 migrations. These delta values were used in the statistical
 analyses. To estimate chlorophyll a concentration at
 surface (5 m), seawater samples of 100 mL were filtered through 25 mm GF/F
 filters (Whatman) in triplicate, extracted in 100% methanol for 24h at
 4°C, and measured fluorometrically with an AU10 Turner Fluorometer (Turner
 Design, Inc.) according to the method by Parsons et al. (1984).
 Euphausiids were sampled using a macrozooplankton net (1 mm mesh
 size, 3.14 m2 opening area) designed for catching large and fast-swimming
 krill and amphipods. The net was deployed oblique from the surface to 20 m
 over the sea floor while the vessel moved at 2knts. Upon retrieval, the
 cod-end was immediately emptied into a container filled with ambient sea
 water, and 10-14 live and actively swimming krill were collected with
 forceps and placed in petri dishes filled with sea water (see sample size
 per station; Table 1). The species was identified under a Leica M50 stereo
 microscope, and an image of each individual was taken when possible.
 Length of each individual was measured from the tip of the rostrum to the
 end of the telson at an accuracy of 1 mm. The individuals were dried with
 tissue paper and stored in 1.5-mL plastic Eppendorf tubes, and frozen in
 -80°C while live. Samples were stored at -80°C until molecular
 analyses. <em>Biomarker
 methods</em> The frozen krill were weighed to get
 the wet weight of each individual and then crushed to powder in a tissue
 lyser (Qiagen) (twice/1 min at 30 shakes per second). Thereafter the
 frozen powder was divided into two sub-samples, one for the energy content
 measurements (lipids, proteins, glycogen and glucose) and one for the
 enzymatic (CS and LDH) and oxidative stress (LPX and Carb) measurements.
 For energy content measurements, samples were homogenized in 1:5 mg µl-1
 0.1M citrate buffer (pH 5.0) using a Bullet Blender (Next Advance, speed
 8, 5 minutes). The samples were aliquoted for protein, lipid, glucose and
 glycogen measurements. The aliquots for glucose and glycogen were boiled
 for 2.5 minutes. <br> For the enzymatic activity and oxidative
 stress measurements, samples were homogenized in 1:5 mg µl-1 of 100 mM
 K-phosphate buffer containing 150 mM KCI (pH 7.4) using a Bullet Blender
 (speed 8, 5 minutes). Aliquots were taken first for lactate dehydrogenase
 (LDH) activity measurements that were further diluted with 50 mM Tris
 solution (pH 7.4). Second aliquots were taken for citrate synthase (CS)
 activity measurements. The remaining samples were further diluted to reach
 1:10 mg of tissue µl-1 of buffer and a third aliquot was taken for lipid
 peroxidation (LPX) analyses. Thereafter the leftovers of the samples were
 centrifuged at +4°C, 10,000g for 15 min and aliquoted for protein
 carbonylation (Carb) and protein measurements. All the samples were
 flash-frozen in liquid nitrogen and stored at -80°C until further
 analyses. CS and LDH are enzymes involved in the
 aerobic and anaerobic metabolism of organisms, respectively. Thanks to the
 measurement of the activity of CS we could evaluate the level of aerobic
 metabolism increase or decrease in response to thermal and salinity
 variation. However, if there is a stressful condition due to exacerbation
 of those environmental conditions the organism could suppress aerobic
 metabolism in favour of the anaerobic metabolism, like glycolysis, whose
 LDH activity is taking part of. The CS enzyme activity measurements were
 done according to Anttila et al. (2013), having following substrate
 concentrations: DTNB 0.17 mM, oxaloacetate 1.9 mM and Acetyl CoA 0.14 mM.
 In the protocol the background signal was determined by measuring the
 absorbance without the addition of oxaloacetate. The LDH enzyme activity
 was also measured according to Anttila et al. (2013) having the following
 substrate concentrations: NADH 0.25 mM and pyruvate-Na 25 mM. In the
 protocol the background signal was determined by measuring the absorbance
 without the addition of pyruvate-Na. Both enzyme activities were done
 using the colour formation and activity was measured for 3 minutes at room
 temperature at a wavelength of 412 nm for CS and 340 nm for LDH. After the
 measurements, the protein concentrations were determined for each sample
 using a PierceTM BCA Protein Assay kit (ThermoFisher), which were used to
 normalise the enzyme activity The activities were calculated per mg of
 protein in samples. Oxidative stress, reported here
 using lipid peroxidation and protein carbonylation, is a response of the
 cells to the negative effect of reactive oxygen species (ROS) produced by
 mitochondria respiration and that are not counteracted by antioxidant
 enzymes. If the production of ROS exceeds the antioxidant counteractive
 capacity, the biomolecules of the cell are depleted, resulting in membrane
 destruction and protein denaturation. Therefore, studying those damage
 would give as a measure of stress of the cell in response to environmental
 stress that is not well counteracted. Lipid peroxidation was determined
 based on the protocol from Vuori & Kanerva (2018), using as
 reagent 2.5 mM ammonium iron (II) sulfate in 0.25 M sulfuric acid and
 0.111 mM xylenol orange in methanol. After two hours of incubation, the
 absorbance of the sample was measured at a wavelength of 570 nm and the
 lipid peroxidation was calculated per mg of protein. Protein carbonylation
 (Carb) was conducted following the instructions of the Protein Carbonyl
 Content Assay Kit from Sigma-Aldrich (MAK094-1KT). The kit is based on the
 principle that carbonyl content is determined by the derivatization of
 protein carbonyl groups with 2,4-dinitrophenylhydrazine (DNPH) leading to
 the formation of stable dinitrophenyl (DNP) hydrazone adducts. It was
 measured by spectrophotometer at 375 nm and the amount of carbonylation
 (in nmol) was expressed per amount of protein (in mg) in the samples
 (measured with BCA kit). Measurement of the energy content could provide
 information about the energy reserves that the organism is consuming in
 response to environmental variation. While glycogen and glucose
 measurement could provide information relative to the fast response to an
 environmental stressor, the lipid and protein content would give more
 insight on the quantity of energy storage depletion in response to a
 prolonged stressful condition. The total lipid content was measured using
 the phospho-vanillin method (Frings et al., 1972) with vanillin reagent
 and phosphoric acid, and the absorbance was measured at 540 nm. Total
 protein content was measured using a protein dye binding method (Protein
 Assay kit, Sigma-Aldrich) and the absorbance was measured at 562 nm. Total
 glycogen and glucose contents were measured using the amyloglucosidase
 method (Carr & Neff, 1984) based on a glucose standard curve and
 as a reagent an O-toluidine mix with acetic acid, measured at 650 nm. The
 energy contents were calculated per g of tissue. For the enzyme activity
 assay (CS and LDH) a plate control sample was used. For oxidative stress
 damage a standard curve was used for LPX assay, while a milliQ-water
 sample + blank + plate control sample were used for Carb assay. For the
 energy content a milliQ-water sample + blank + standard curve + a plate
 control sample were used for glycogen and glucose, while a milliQ-water
 sample + standard curve were used for lipids. For BCA protein assay a
 standard curve only was used. <em>Statistical
 analyses</em> All the statistical analyses were
 conducted in RStudio using the R version 4.2.2 (‘R: The R Project for
 Statistical Computing’). To see if mass, length, energy content, energy
 metabolism and oxidative damage of krill differed among stations, we ran a
 one-way ANOVA test. Thereafter, we investigated in more depth whether the
 type of water mass (Arctic, Mixed or Atlantic) shaped the biological
 responses. The fjords were divided into different types as indicated in
 Table 1. The definitions were based on the water temperatures and
 salinities during the sampling time; see Results section. Thereafter, a
 one-way ANOVA test was run using the water type as categorical variable
 (Atlantic, Arctic and Mixed). If there were significant differences among
 stations and water types, the pairwise contrasts were analysed using the
 Tukey’s test. A general linear model was used to
 analyse how <em>T. inermis</em> was influenced by variation
 (delta, i.e., difference between highest and lowest observed value within
 station) in temperature and salinity that they encounter during diel
 vertical migration. The models were run for each biological response
 (lipid, protein, glycogen and glucose content, as well as CS and LDH
 activity, and LPX and Carb amount) using the environmental variables
 (delta salinity and delta temperature; see Table 1) as fixed effect,
 against each biological response as dependent variable. The models
 included the depth of the station, chlorophyll <em>a</em>
 concentration and the mass of individuals as co-factors. The depth was
 included into the model due to the high variability in the depth between
 the stations (123 to 326 m). Furthermore, since the mass of krill was
 found to be significantly different among stations and water masses, and
 because mass also could influence the energetics of krill, it was included
 in the model as covariate. Similarly, chlorophyll <em>a</em>
 concentration varied among the stations; thus, it was included into the
 model since food availability could influence the measured biological
 variables. We performed a model selection followed by a step-by-step
 approach based on the Akaike Information Criterion (AICc), which was
 obtained by running the function <em>compare_performance</em>
 in package performance (Lüdecke et al. 2021). First, we tested which
 combination of the co-factors in the model (having delta temperature and
 salinity as fixed effects in interaction) had the lowest AICc values. The
 best model was kept for the next step where it was evaluated whether the
 interaction effect or the additive model (i.e., without interaction
 effect) of delta salinity and temperature resulted in lower AICc value.
 The final model for each biological variable was determined by the lowest
 AICc value. Each model residual distribution was visually assessed using
 the function <em>simulateResiduals</em> in DHARMa R package
 (F. 2018). The model selection for each biological variable is shown in
 Supplementary Table S1. The final models are shown in Table 2. In all
 statistical tests significance was considered at <em>p &lt;
 0.05</em>. The model outputs were plotted using the
 <em>ggplot2</em> package (Wickham, 2016). 
description: # Salinity-temperature interaction drives metabolic and energetic changes
 in an Arctic crustacean
 [https://doi.org/10.5061/dryad.44j0zpcr4](https://doi.org/10.5061/dryad.44j0zpcr4) ## Description of the data and file structure ### Files and variables #### File: R_dataset_Ecosphere.csv **Description:** This dataset contains all the environmental variables collected during the Svalbard cruise and the results from each biomarker. The dataset is semicolon-delimited with commas as the decimal. n/a values indicate "not available" data (not enough sample for performing the assay). ##### Variables * Station (location where krill were sampled): Rijpfjorden, Storfjorden, Kongsfjorden, Isfjorden, WaF (Wahlenbergfjorden), Hinlopen; * Fjord type (type of fjord classification based on previous and current data present in the study): Arctic, Mixed, Atlantic; * Station number (number of the location): 1-6; * Krill (name of each krill individual); * mass: mass of each krill in mg * length: length of each krill in cm * EC_protein_mg/g: total protein concentration for each krill , expressed in mg/g * lipid_mg/g: total lipid concentration for each krill, expressed in mg/g * glycogen_mg/g: total glycogen concentration for each krill, expressed in mg/g * glucose_mg/g: total glucose concentration for each krill, expressed in mg/g * CS_act: enzymatic activity of citrate synthase (mol/min mg-1) * LDH_act: enzymatic activity of lactate dehydrogenase (mol/min mg-1) * LPX: Lipid peroxidation (mg/g) * Carb: Protein carbonhylation (nmol/mg) * Deepness_net: Depth of the net used to sample the krill (m) * Chl_a_50: amount of chlorophyll a at 50 m depth [µg L-1] * Chl_a_20: amount of chlorophyll a at 20 m depth [µg L-1] * Chl_a_5: amount of chlorophyll a at 5 m depth [µg L-1] * Temp_average: average temperature relative to each station (degree Celsius) * Sal_average: Salinity average relative to each station (ppt) * Temp_max: Maximum temperature in each station (degree Celsius) * Sal_max: Maximum salinity in each station (ppt) * Temp_min: Minimum temperature in each station (degree Celsius) * Sal_min: Minimum salinity in each station (ppt) * Temp_delta: Delta (max - min) temperature (degree Celsius) * Sal_delta: Delta (max - min) salinity (ppt)