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Description    UNFORMATTED ATTACHMENT PREVIEW Name: ___________________________________________ Date: _______________________ Reading and Analyzing a Scientific Journal Article Use the following questions to help you work through the posted journal article. You will then complete the write-up assignment (on page 2 of this document). You will submit this sheet with your answers typed along with your write up. 1. Abstract a. What do the authors state is the purpose or hypothesis that they are testing in the study? (Write down the exact sentence where the authors describe what they are doing in the study. Include quotation marks.) b. What is the current gap in knowledge that the authors are trying to address with their study? c. What experimental tools or measurements did the authors use in their methods to test their hypothesis. d. What do the authors say are the major conclusions or findings of the study? Include quotation marks where appropriate. e. What are the significant contributions of this study to the scientific literature at large? 2. Introduction a. What is the big picture problem that led the authors to study this particular research question? (Impact/Relevance…Why should the reader care about the study?) b. What have previous studies demonstrated in relation to the big picture problem? c. What are the specific gaps in the current knowledge that the authors are trying to address? d. What is the experimental organism being used? What are its advantages and disadvantages? (Why did the authors choose this organism?) e. What do the authors say are the major conclusions or findings of the study? Include quotation marks and page numbers where appropriate. Name: ___________________________________________ Date: _______________________ 3. Results a. Figure 2a & 2b (section 3.1) i. What is the experimental question being asked? ii. What is being measured? iii. What are the controls and experimental groups? (ambient temperature is 14ºC and pCO2 is 365uatm; 2100 predicted temperature is 21.5ºC and pCO2 is 1050uatm) iv. What are the key results of the figure? v. What is the conclusion of the figure? b. Figure 3a (section 3.4) i. What is the experimental question being asked? ii. What is being measured? iii. What are the controls and experimental groups? (ambient temperature is 14ºC and pCO2 is 365uatm; 2100 predicted temperature is 21.5ºC and pCO2 is 1050uatm) iv. What are the key results of the figure? v. What is the conclusion of the figure? 4. Discussion a. What do the authors claim are the three “fundamental insights” emerging from this work? b. Shell integrity and growth (section 4.1) i. What are the key conclusions? ii. What do the authors suggest is the relevance of their findings? iii. What areas of future study resulted from this work? c. Energy reserves and metabolism (section 4.2) i. What are the key conclusions? ii. What do the authors suggest is the relevance of their findings? iii. What areas of future study resulted from this work? d. Based on your understanding of the figures, do you agree or disagree with the authors conclusions? Write-up Assignment: Reading and Analyzing a Scientific Journal Article In your own words write a maximum of two pages (double spaced) to summarize the article you were assigned. The write-up should summarize the article that you read. Be sure your summary answers the following questions but should NOT just be direct answers to these questions. What is the purpose of the study? What are the major results? What is/are the key experiments/figure from the article? What is/are the main conclusions? Comparative Biochemistry and Physiology, Part A 240 (2020) 110579 Contents lists available at ScienceDirect Comparative Biochemistry and Physiology, Part A journal homepage: www.elsevier.com/locate/cbpa Ocean acidi?cation and warming e?ects on the physiology, skeletal properties, and microbiome of the purple-hinge rock scallop? T ? Lindsay Almaa,b, , Karin E. Kramb, Gordon W. Holtgrievea, Ashley Barbarinob, Courtney J. Fiamengoa,b, Jacqueline L. Padilla-Gamiñoa,b a b School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98105, USA Department of Biology, California State University, Dominguez Hills, Carson, CA 90747, USA A R T I C LE I N FO A B S T R A C T Keywords: Bivalve Multiple stressors Fatty acids Shell strength CT scan Metagenomics Ocean acidi?cation and increased ocean temperature from elevated atmospheric carbon dioxide can signi?cantly in?uence the physiology, growth and survival of marine organisms. Despite increasing research e?orts, there are still many gaps in our knowledge of how these stressors interact to a?ect economically and ecologically important species. This project is the ?rst to explore the physiological e?ects of high pCO2 and temperature on the acclimation potential of the purple-hinge rock scallop (Crassadoma gigantea), a widely distributed marine bivalve, important reef builder, and potential aquaculture product. Scallops were exposed to two pCO2 (365 and 1050 ?atm) and temperature (14 and 21.5 °C) conditions in a two-factor experimental design. Simultaneous exposure to high temperature and high pCO2 reduced shell strength, decreased outer shell density and increased total lipid content. Despite identical diets, scallops exposed to high pCO2 had higher content of saturated fatty acids, and lower content of polyunsaturated fatty acids suggesting reorganization of fatty acid chains to sustain basic metabolic functions under high pCO2. Metagenomic sequencing of prokaryotes in scallop tissue revealed treatment di?erences in community composition between treatments and in the presence of genes associated with microbial cell regulation, signaling, and pigmentation. Results from this research highlight the complexity of physiological responses for calcifying species under global change related stress and provide the ?rst insights for understanding the response of a bivalve's microbiome under multiple stressors. 1. Introduction Anthropogenic activities have exponentially increased the carbon dioxide concentration in the atmosphere since the beginning of the Industrial Revolution. Increased CO2 contributes to the “greenhouse” e?ect which causes the atmosphere and oceans to warm. Higher levels of CO2 in the atmosphere lead to higher dissolution of CO2 into the ocean. Increased CO2 dissolution into the ocean can change carbon chemistry, making water more acidic and reducing calcium carbonate availability which is critical for many marine calci?ers (Doney et al., 2009). As the Anthropocene progresses and carbon dioxide levels continue to increase, it is vital that we understand how di?erent stressors associated with increased levels of pCO2, such as ocean warming and ocean acidi?cation, may interact (or not) and impact the performance of marine species. Identifying limits of physiological ?exibility under multiple stressors will help to develop models to realistically predict how species will perform, allocate energy, adapt, and survive in an increasingly changing environment (Sebens et al., 2018). This will help us to quantify tolerance limits and determine under what circumstances the stressors act additively, antagonistically, or synergistically (Gunderson et al., 2015; Todgham and Stillman, 2013). Consequences of decreased physiological and organismal performance metrics in marine organisms due to changing ocean conditions have the potential to negatively impact associated food webs and local human economies. Previous studies have shown that ocean warming and acidi?cation usually interact additively or synergistically to reduce marine invertebrate ?tness. In bivalves, ocean acidi?cation can narrow the thermal tolerance range, resulting in a higher susceptibility to extreme temperatures and impairment in organismal performance (Schalkhausser et al., 2013). Hard shell clams exposed in the laboratory to increased pCO2 and thermal stress lead to higher organismal energy ? This article is part of a special issue entitled: Mechanisms of biological sensitivity and resistance to a rapidly changing ocean, edited by: Dr. Logan Cheryl, Dr. Evans Tyler and Dr. Mike Hedrick ? Corresponding author at: School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98105, USA. E-mail address: lalma@uw.edu (L. Alma). https://doi.org/10.1016/j.cbpa.2019.110579 Received 2 May 2019; Received in revised form 5 September 2019; Accepted 11 September 2019 Available online 16 September 2019 1095-6433/ © 2019 Elsevier Inc. All rights reserved. Comparative Biochemistry and Physiology, Part A 240 (2020) 110579 L. Alma, et al. integrity and microbiome of C. gigantea. We sought to address the following questions: (i) To what extent are shell strength and skeletal density a?ected by multiple global change stressors in C. gigantea? (ii) What are the physiological impacts of simultaneous exposure of multiple stressors in terms of energy reserves and allocation? (iii) How is the microbiome of C. gigantea a?ected by exposure to ocean warming and ocean acidi?cation? Results from this study provide insights into physiological tolerance of C. gigantea when subjected to near-future OA and OW conditions and long and short-term consequences to their ?tness. demands to maintain basic metabolism (Matoo et al., 2013). Decreased ?tness was observed in the common cockle which were exposed simultaneously to high pCO2 and high temperature, where energy uptake and shell strength was reduced, and respiration increased (Ong et al., 2017). In sea urchin larvae, simultaneous exposure to increased temperature and pCO2 signi?cantly reduced larval metabolism (PadillaGamiño et al., 2013). Marine bivalves are ecologically and economically important calci?ers that are currently being severely impacted by climate change related stressors (Barton et al., 2015; Talmage and Gobler, 2011). Previous studies have shown that near future ocean warming (OW) and ocean acidi?cation (OA) levels predicted by year 2100 will negatively alter bivalve metabolism (Ivanina et al., 2013; Matoo et al., 2013; Timmins-Schi?man et al., 2014), decrease shell integrity and impair biomineralization (Wright et al., 2018; Duckworth and Peterson, 2013; Mackenzie et al., 2014a; Rühl et al., 2017), and cause the organism to be more susceptible to disease (Burge et al. 2014, Mackenzie et al., 2014b, Fuhrmann et al., 2019). To date, however, many knowledge gaps remain, speci?cally in the linkages between cellular metabolism, energy allocation and stress tolerance (Sokolova et al., 2012). Another important gap in our understanding is how a bivalve's microbiome will respond to OA and OW, and if virulent microbes in shell?sh will become more prevalent under global change scenarios. Studies on shell?sh microbial responses to single stressors have just begun to emerge; Asplund et al. (2014) found that a four-month exposure of blue mussels (Mytilus edulis) to OA caused a higher incidence of the virulent microbe Vibrio tubiashii; and Fuhrmann et al. (2019) resolved that paci?c oysters, Crassostrea gigas, exposed to OA treatment had a lower survival rate when exposed to Ostreid herpesvirus type I than those who were not subjected to OA. The purple-hinge rock scallop Crassadoma gigantea (Fig. 1a, b) (Gray 1825, formerly Hinnites multirugosus, Gale 1928) is widely distributed across the North American Paci?c Coast from Southern Alaska to Baja California, Mexico. They can be found from lower intertidal to 80 m depth (Bourne, 1987; Whyte et al., 1990). C. gigantea are ecosystem engineers – they form the foundation of reef structures by clustering on rocks, pilings, and oil rigs and provide habitat for thousands of organisms (Fig. 1c) (Laurén, 2008). Unlike other scallop species which have the ability to swim, C. gigantea permanently attach to hard substrate, making it very di?cult to actively avoid unfavorable ocean conditions (Culver et al., 2006; RaLonde, 2012). C. gigantea is of interest in the aquaculture industry and is considered a seafood delicacy due to its large, sweet-tasting adductor muscle. Despite their ecological importance and growing interest in the aquaculture industry, to the authors' knowledge, there has not been any published research involving the impacts of global change on this species. These scallops are, and will further be, subject to OA and temperature stress throughout their native range along the California Current Large Marine Ecosystem (CCLME), which may a?ect the reefs they sustain and their future as a harvested aquaculture species (Filgueira et al., 2016). Due to the topographic and geographic nature of the CCLME, this area has already experienced increased upwelling (lowering the pCO2 levels) and warming events. This was exempli?ed during the marine heatwave of 2013–2016 where we observed high temperature anomalies in the CCLME of 1.5 °C to 6.2 °C (Bond et al., 2015; Di Lorenzo and Mantua, 2016). Studies predict that the CCLME will begin to experience summertime aragonite undersaturation within the optimal habitat depths of C. gigantea by year 2050 (Gruber et al., 2012; Hofmann et al., 2014). In this study we used a multidisciplinary approach to understand the physiological response of C. gigantea under ocean warming and ocean acidi?cation. Stressful conditions may cause organisms to reallocate their energy to sustain basic metabolic functions and this in turn can compromise other processes such as calci?cation, immunity, or growth. This study provides the ?rst insights into the interactive e?ects of ocean warming and ocean acidi?cation on the physiology, shell 2. Methods and materials 2.1. Specimen collection and experimental conditions Mature adult C. gigantea were collected by SCUBA divers (scienti?c permit No. SC-9758) at 23–25 m depth on August 1, 2016. Collection site was located at Eureka Oil Rig, o?shore of Huntington Beach, California (33.56405° N, 118.1158° W). Scallop shell height ranged from 4.1 to 17 cm with an average of 9.5 cm ± 2.7 cm (SD), and shell width range from 15.1 to 3.4 cm with an average of 9.4 cm ± 2.2 cm (SD). Scallops are estimated to be 5 years old on average based on a growth chart published by MacDonald et al. (1991). Following collection, scallops were scraped clean of epibionts and transported into saltwater tanks within 1 h of collection. Scallops were measured and labeled with Milliput epoxy putty. The organisms were then placed in eight 60 L tanks ?lled with arti?cial sea water (n = 7–8 per tank) and allowed to acclimate to ambient conditions (14 ± 0.02 °C and pCO2 ~365 ?atm) for one week prior to experimental treatments. Scallops were fed using Shell?sh Diet 1800 (Reed Mariculture, Campbell, CA: 40% Isochrysis galbana, 25% Tetraselmis, 20% Thalassiosira pseudonana, and 15% Pavlova lutheri). The room was kept on a 14:10 h light: dark cycle and salinity was held constant at 33 ± 1 PSU. Following acclimation, scallops were held for six weeks in one of four treatments: (1) 21.5 °C, 1050 ?atm, (2) 21.5 °C, 365 ?atm, (3) 14 °C, 1050 ?atm, and (4) 14 °C, 365 ?atm, which represent factorial combinations of ambient conditions and predictions for year 2100 (IPCC, 2013; Stocker et al., 2013). pCO2 was controlled in each tank by injecting a slow stream of CO2 gas to a select threshold via a solenoid regulator system in accordance with the Standard Operating Procedure (SOP) for Ocean CO2 Measurements (Dickson and Sabine, 2007). All tanks were controlled for temperature individually using a closed loop heating and chilling system. Each treatment was performed in replicate, and each tank was completely independent of one another, with separate chillers, heaters, and CO2 systems (Appendix S1, Fig. S1). Water samples were collected weekly and poisoned with 100 ?L of saturated mercuric chloride (HgCl2) in accordance with Dickson and Sabine (2007). Samples were tested for alkalinity using 2320 B open cell titration method (APHA 2012). Temperature, salinity, and carbonate chemistry (calculated using CO2calc software, USGS, Robbins et al., 2010) of seawater used in experimental treatments can be found in Appendix S1, At the end of the six-week experiment, scallops were removed from their tanks (5–7 individuals per tank), dissected, weighed for wet weight, and samples of ctenidia (gill), adductor muscle, gut, and remaining viscera were ?ash frozen with liquid nitrogen and stored at ?80 °C. Shells were cleaned of any tissue using a soft cloth and stored dry. 2.2. Shell strength analysis All shells (n = 14 individuals per treatment) were rehydrated for 24 h in seawater before performing shell strength tests (Ikejima et al., 2003). Each shell was marked using a paint marker at four equally spaced points across its length. A Universal Testing Machine (Instron, model 5585H) was ?tted with a 3.9 mm cylindrical steel punch and 2 Comparative Biochemistry and Physiology, Part A 240 (2020) 110579 L. Alma, et al. Fig. 1. (a) C. gigantea shell, (b) andinterior (~15 cm), (c) C. gigantea serves host to epibionts (~7 cm). (Micro-CT) scanner (Skyscan model 1173, Burker, Belgium) to determine relative shell density. Dried shells (n = 14 per treatment) were scanned at an X-ray resolution of 1120 × 1120 using a 1 mm aluminum ?lter, a voltage of 65 or 70 kV, and a current of 114 or 123 ?A for thinner and thicker shells, respectively. Two phantom rods (SP-4003 Burker, Belgium) of known volumetric density (0.25 and 0.75 g/cm3) were scanned alongside shells for calibration purposes. Horizontal 2-D stacked images were re-projected into a 3-D image using Burker's NRecon software based on a modi?ed Feldkamp's algorithm (Feldkamp et al., 2008). To measure relative shell mineral density (g/cm3), each 3-D image was calibrated by isolating phantom rods into a region of interest (ROI) and entering their known densities and attenuation coe?cients (mm?1) into a calibration algorithm within Burker's CT Analyzer v.1.16 software. Ten vertical 2-D cross sections were randomly selected throughout the length of each shell, and the total shell density was measured by tracing a ROI around the perimeter of the shell (Chatzinikolaou et al., 2017; Queirós et al., 2015). To compare the density of the periostracum (rough outer layer of the shell exposed to the water) to the overall shell density, 15 pixels were selected as the ROI along the outside of the shell (Papageorgiou and Schmidbaur, 2014; Rühl et al., 2017). The ratio of periostracum to total shell density corresponded to the relative dissolution of the outer shell. 4.76 mm die (Carnarius et al., 1996; Ikejima et al., 2003; Wilkie and Bishop, 2012). Shells were removed from the saltwater and immediately placed onto the stage, with the inner side facing upward on a marked point and held perpendicular to the Instron plate. The crosshead was lowered onto the scallop shells at 5 mm s?1, and the force (N) needed to puncture the shell was recorded using Bluehill Software (v.2) (Illinois Tool Works Inc., IL, USA). The puncture force (N) was averaged among 8 puncture points per individual, the 4 punctures made in each shell and in both shell vales of each individual. Shell thickness was measured at the eight marked points using a digital outside caliper gauge (0.01 mm accuracy). Shell strength at each point was calculated using the following formula (Carnarius et al., 1996; Ikejima et al., 2003; Tyler, 1961): S= F ?dt where S is shell strength measured in megapascals (N mm?2), F is the maximum penetrating force (N), t is the shell thickness (mm), and d is the diameter of the punch (mm) multiplied by pi to get the circumference of the punch. Shell thickness and maximum force for each treatment were correlated using a linear regression (So?e Grefsrud and Strand, 2006; Wilkie and Bishop, 2012). 2.3. Micro-CT scanning Shells were scanned using a micro computerized tomography 3 Comparative Biochemistry and Physiology, Part A 240 (2020) 110579 L. Alma, et al. replicate as a random e?ect and temperature and pCO2 as ?xed e?ects using the lmer function from the library lme4 (Bates et al., 2014). Hypotheses testing was conducted based on the ?xed e?ects only using a two-way ANOVA. Post-hoc Tukey HSD tests (corrected for multiple comparisons) was performed to determine di?erences among treatments. A Shapiro-Wilk test was performed to assess normality of the data, and a Levene's test was performed to con?rm homogeneity of variance. If needed, values of analysis were log transformed to achieve normality assumptions before the model was run. A non-metric multidimensional scaling analysis (NMDS) was performed using metaMDS Bray-Curtis dissimilarity and oridhull functions within vegan library in R (Oksanen et al., 2013) and was used to visualize distribution of FAs and microbes among treatments (Galloway et al., 2015; TimminsSchi?man et al., 2014). FA's and bacterial community di?erences among treatments were analyzed using a ?xed factor permutational multivariate analysis (PERMANOVA) using R vegan adonis function with 10,000 random permutations of the residuals under the reduced model (Lamb et al., 2017). Shannon index of microbes was calculated using the R vegan diversity function. Both Sorenson and Bray-Curtis dissimilartiy indices were calculated using the “beta-pair” or “bray.part” function of the R betapart package (Baselga and Orme, 2012) and the vegan betadisper function. 2.4. Total lipid and fatty acid analysis Ctenidia and adductor muscle tissue were freeze dried for 48 h and ground using a ball mill (Soudant et al., 1999; Tocher and Sargent, 1984; Whyte et al., 1990). A microbalance (sensitivity 10 ?g) was used to measure 15 g of ground adductor mussel and ctenidia powder within pre-weighed aluminum tins. Total lipids (n = 11–14 per treatment, 5–7 per tank) were extracted in accordance with methods from Bligh and Dyer (1959). In short, two puri?cation cycles of a 2:1 chloroform/ methanol solution and ultrapure water were performed to separate the lower chloroform phase containing the lipids from the rest of the tissue. Total lipids were determined gravimetrically by drying and weighing a subsample. The relative composition of 14–24 carbon chain fatty acids (FA) of each individual was determined by transmethylation of dry ctenidia lipid samples by acid-catalyzed esteri?cation with a 1% sulfuric acid in methanol incubated at 50 °C for 16 h and extracted into fatty acid methyl esters (FAME) in accordance with methods from Christie (1998). FAMEs were analyzed using a ?ame ionization detector gas chromatograph (GC) (HP 6890, Agilent DB-23 column 30 m length, 0.25 mm diameter, 0.15 ?m ?lm thickness), and output chromatograph peaks were identi?ed with a FA standard mixture (37-component FAME, Supelco, Bellefonte PA) (Galloway et al., 2015). An individual's FA pro?le was interpreted using a printed output chromatograph and calculated by normalizing each FA peak area by the sum of all FA peak areas. 3. Results 3.1. Shell strength 2.5. Microbial enrichment and DNA extraction To examine microbial taxonomy and functions, ctenidia and gut tissue (n = 3 per treatment and tissue) were homogenized using a sterile disposable mortar and 1.7 mL micro-centrifuge tube. During homogenization 500 mL NaCl saline (8.5%) bu?er was added to the tissue. The homogenates were centrifuged at 1000 RPM for 5 min to pellet the large tissue debris. The supernatant was transferred to a new micro-centrifuge tube and centrifuged at 10,000 RPM for 20 min to pellet bacterial cells (Oliveira et al., 2013). Genomic DNA was extracted from this pellet with the DNeasy Blood and Tissue kit (Qiagen Valencia, CA, USA) following the Gram-positive bacteria protocol. Both, high pCO2 and high temperature decreased shell strength (p < .001, p = .011, Fig. 2a, Table 1). At ambient temperature (14 °C), shell strength decreased by 24% under high pCO2 whereas at high temperature (21.5 °C), shell strength decreased by 19% under high pCO2 (Fig. 2a). The interaction between pCO2 and temperature was not signi?cant, indicating no synergistic e?ect (p = .606, Table 1). Linear regression analyses revealed that the force needed to puncture the shell was positively correlated with shell thickness (p < .001, Fig. 2b). In this and all other analysis, no signi?cant di?erences between replicate tanks were observed. Additional variance from multiple tanks was estimated to be zero, indicating no e?ect of tank on the response variables. 2.6. Illumina metagenomic sequencing and bioinformatic analysis 3.2. Scallop growth Extracted genomic DNA was prepared for sequencing using the Illumina NexteraXT library preparation kit. Prepared libraries were normalized and pooled and sequenced on the Illumina HiSeq 4000, with 150 bp paired end reads. Quality of sequencing reads were assessed with FastQC (Andrews and Bioinformatics, 2010). Taxonomic and functional classi?cations were run using the InsideDNA cloudbased platform (https://insidedna.io). Reads were classi?ed against the bacteria NCBI-database at the species and family level using the classify_metagenome script from CLARK 1.2.4 (Ounit et al., 2015). Wet weigh of scallops did not change between treatments after 6 weeks (p = .88). We performed shell length and width measurements before and after the experiment and we did not detect any growth during the 6-week experiment (on a millimeter scale). 3.3. Micro-CT scanning DIAMOND 0.9.18 (Buch?nk et al., 2014) was used to align sequences against nr (non-redundant protein sequences) database using the script diamond blastx –db nr.dmnd. MEGAN 6.10.10 (Huson et al., 2007) with SEED (Overbeek et al., 2014) database was used to get functional classi?cation using the script daa2rma -a2seed acc2seedMay2015XX.abin. Micro-CT scanning results revealed no signi?cant di?erences in overall shell density between treatments (p = .294, p = .793 for pCO2 and temperature respectively, Table 1). However, there was a 14.6% reduction in the ratio of periostracum density:total shell density in scallops acclimated to high pCO2 (p < .001 Fig. 2c, Table 1), suggesting that dissolution may occur primarily in this upper layer as opposed to the deeper layers of the shell. The interaction term between pCO2 and temperature was not signi?cant, indicating no synergistic e?ect (p = .355, Table 1). Additional variance from multiple tanks was estimated to be zero, indicating no e?ect of tank on the response variables. 2.8. Statistical analysis 3.4. Total lipid and fatty acid analysis Statistical analyses on shell strength, CT-scans, lipid, FAs, and bacterial metagenomics were performed in R Version 3.5.3. We applied a linear mixed e?ects model for each response variable with tank Total lipid content was 30.6% higher in the ctenidia than the adductor muscle (p < .001). Increased pCO2 had a signi?cant e?ect on lipids in both ctenidia and adductor muscle (p < .001). Total lipid 2.7. Functional annotation 4 Comparative Biochemistry and Physiology, Part A 240 (2020) 110579 L. Alma, et al. 5000 25 (a) bc (b) 21.5°C/1050 µatm 21.5°C/365 µatm 14°C/1050 µatm 14°C/365 µatm 4000 ab ab Maximum load (N) Mega Pascals (N/mm2) 20 a 15 10 3000 2000 2 R = 0.41 2 R = 0.52 2 R = 0.60 2 R = 0.62 1000 5 0 0 2 4 6 8 10 Fig. 2. Values given as means ± S.E. (n = 14 individuals per treatment). Di?erent letters indicate signi?cant di?erences (p < .05). (a) Force needed to puncture a shell at 4 points across the length, normalized by thickness of the shell (mega pascals), (b) Relationship between shell thickness (mm) and maximum load (N) needed to puncture C. gigantea shells. The force needed to puncture the shell was positively correlated with shell thickness. Each point represents one puncture point, and each shell was punctured 4 times and averaged for statistical analysis. (c) Ratio between C. gigantea periostracum and overall shell density after six-week exposure to temperature and pH treatments. (d) A rock scallop shell reprojected and colored using micro-CT imaging and software. 12 Shell thickness (mm) 0 Periostracum/Total Density (g/cm³) 1.2 (d) (c) b b 1 ab a 0.8 0.6 0.4 0.2 0 1 cm 1050 µatm 365 µatm 21.5°C 1050 µatm 365 µatm 14°C content was not signi?cantly a?ected by temperature, nor the interaction term in either tissue type (Fig. 3a, Table 1). Additional variance from multiple tanks was estimated to be zero, indicating no e?ect of tank on the response variables. Despite identical diets, twenty-?ve individual fatty acid peaks were isolated in the GC pro?les of scallop ctenidia (Table 2). Eight FAs had signi?cant di?erences between treatments in the three major classes: saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA). FAs that had signi?cant di?erences (p < .05) between treatments were pentadecanoic acid 15:0 (derived from gut dwelling bacteria), iso-16:0 (derived from gut dwelling bacteria), 18:0 (stearic acid), 20:0 (gadoleic acid), 16:1?7 (palmitoleic acid), 16:2?4 (9,12-hexadecadienoic acid), 18:2?6 (linoleic acid), and 22:5?6 (Docosapentaenoic acid). NMDS analysis of ctenidia FAs (Bray Curtis stress = 0.079) showed high similarity between the samples from the control group (14 °C/365 ?atm) and low similarities among samples exposed to high temperature (21.5 °C) (Fig. 3b). A PERMANOVA comparing the diversity of FA biomarkers between treatments revealed no signi?cant interaction of pCO2 and temperature (p = .183, R2 = 0.0312). Scallops exposed to high pCO2 had 31.7% and 14.7% less PUFAs (21 °C and 14 °C, respectively) compared to the ambient pCO2 treatment. Table 1 Summary of Two-Way ANOVA statistics used in this study. Bolded terms indicate a signi?cant di?erence (p < .05). df Mean Sq F value p Shell strength pCO2 Temperature Temperature: pCO2 Residuals 1 1 1 52 0.171 0.0867 0.0001 0.01249 13.706 6.943 0.0154 < 0.001 0.0110 0.902 Total shell density pCO2 Temperature Temperature: pCO2 Residuals 1 1 1 50 0.0431 0.00265 0.0894 1.123 0.0693 2.336 0.294 0.793 0.133 Periostracum:total shell density pCO2 1 Temperature 1 Temperature: pCO2 1 Residuals 50 0.0244 0.00933 0.014 0.0161 15.179 0.580 0.871 < 0.001 0.451 0.355 Total lipids gill pCO2 Temperature Temperature: pCO2 Residuals 1 1 1 48 0.115 0.0347 0.0322 0.0055 21.678 6.532 6.057 < 0.001 0.0609 0.0675 Total lipids adductor pCO2 Temperature Temperature: pCO2 Residuals 1 1 1 50 0.349 0.00281 0.0323 0.0302 11.536 0.0931 1.0686 < 0.001 0.761 0.306 3.5. Microbial analysis We analyzed changes in the bacterial community of scallops by performing metagenomic sequencing of both ctenidia and gut tissues. Fig. 4 shows bacterial diversity of each family in both tissue types. Most samples have a similar bacterial community, however there are a few samples that have one dominant taxon. Overall, we can de?ne several 5 Comparative Biochemistry and Physiology, Part A 240 (2020) 110579 L. Alma, et al. % Total lipids 12 a A Fig. 3. (a) Percent total lipids in ctenidia (solid) and adductor muscle (shaded), analyzed from each treatment. Values given as means ± SE (n = 11–14 individuals per treatment). Di?erent letters indicate signi?cant di?erences (lowercase for ctenidia, uppercase for adductor muscle) (p < .05). (b) Nonmetric multidimensional scaling (NMDS) analysis comparing fatty acid pro?les of ctenidia. (b) Ctenidia Adductor Muscle 0.2 16 b b b B B B 8 NMDS2 0 0.1 (a) -0.1 4 0 Stress= 0.079 n = 51 1050 µatm 365 µatm 1050 µatm 365 µatm 21.5°C -0.06 -0.04 -0.02 0 0.02 21.5°C/1050 µatm NMDS1 21.5°C/365 µatm 14°C/1050 µatm 14°C/365 µatm 14 °C 0.04 0.06 treatments, Vibrionaceae was the dominant family in individuals exposed to 21.5 °C, while those exposed to the 14 °C treatment had the highest occurrence of Propionibacteriaceae. Vibrionaceae made up an average of 18% of the bacterial community in the 21.5 °C treatments when compared to individuals exposed to 14 °C where Vibrionaceae prevailing bacterial families present in every individual including Propionibacteriaceae, Mycoplasmataceae, Flavobacteriaceae, Shewanellaceae, Pasteurellaceae, Streptococcaceae, Alteromonadaceae, Rhodobacteraceae, Enterobacteriaceae, and Mycobacteriaceae; each of these families made up at least 2% of total microbial diversity. Within Table 2 Total lipids expressed as mg/g of total ctenidia tissue dry weight. Fatty acids reported as normalized values from % of total FA peak areas identi?ed (mean ± s.d.). Trace amounts of FAs < 0.5% of total omitted (—). Di?erent letters indicate signi?cant di?erences, corrected for multiple comparisons (p < .05). Bolded fatty acids signi?cant di?erences between treatments (Tukey HSD). 14 °C/365 ?atm 14 °C/1050 ?atm 21.5 °C/365 ?atm 21.5 °C/1050 ?atm n = 14 n = 11 n = 12 n = 14 c Total Lipid (mg/g DW) 98.3 ± 4.2 Saturat

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