Community Characteristics and Ecological Roles of Bacterial Biofilms

Journal of Environmental Management 250 (2019) 109459

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Journal of Environmental Management

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Research article Community characteristics and ecological roles of bacterial bioﬁlms associated with various algal settlements on coastal reefs T

∗ ∗∗ Jialin Lia,b,1, Ting Wangc,d,1, Shuxian Yua, Jie Baic,d, , Song Qina,b, a Key Lab of Coastal Biology and Biological Resource Utilization, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264000, Shandong, China b Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China c College of Environmental Science and Engineering, Ocean University of China, Qingdao, 266100, China d Key Lab of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, Qingdao, 266100, China

ARTICLE INFO ABSTRACT

Keywords: Bacterial biofilms, which are a group of bacteria attaching to and ultimately forming communities on reefs, Algal-bacterial symbiosis perform essential ecological functions in coastal ecosystems. Particularly, they may attract or repulse the settling Reciprocal interaction down of opportunistic algae. However, this phenomenon and the interaction mechanism are not fully under- Coastal reef community stood. This study investigated reefs from the Changdao coastal zone to determine the structures and functions of Biochemical cycling bacterial biofilms symbiosing with various algae using high-throughput sequencing analysis. The Shannon di- Metagenomic analysis versity index of microbiota with algal symbiosis reached 5.34, which was higher than that of microbiota wherein algae were absent (4.80). The beta diversity results for 11 samples revealed that there existed a separation between bacterial communities on reefs with and without attached algae, while communities with similar algae clustered together. The taxa mostly associated with algae-symbiotic microbiota are the Actinobacteria phylum, and the Flavobacteriia and Gammaproteobacteria classes. The Cyanobacteria phylum was not associated with algae-symbiotic microbiota. As revealed by functional analysis, the bacteria mostly involved in the metabolism of sulfur were represented by brown and red algae in the biofilm symbiosis. Bacteria related to the metabolism of certain trace elements were observed only in specific groups. Moreover, phototrophy-related bacteria were less abundant in samples coexisting with algae. This study established the link between bacterial biofilms and algal settlements on costal reefs, and revealed the possible holobiont relationship between them. This may provide new technical directions toward realizing algal cultivation and management during the construction of artificial reef ecosystems.

1. Introduction adhesion of communities has various consequences on the environment of substrates, including the decomposition of inorganic substances (Xu The formation of bacterial biofilm in the marine ecosystem is ubi- et al., 2015), metabolism of organic substances, and circulation of quitous and characterized by a complicated and integrated process. various nutrient elements (Butturini et al., 2000). Because the micro- Originally, a small group of planktonic bacteria adhere together by environment tends to be stable and suitable, biofilms can induce the secreting protective extracellular polymeric substances consisting of attachment of additional organisms (Koo et al., 2017) and the settle- polysaccharides, proteins, and nucleic acids (Gutierrez-Pacheco et al., ment of algae (Seyedsayamdost et al., 2011). 2018). The bacterial assembly gradually proliferates and attaches to Reciprocal relationships between bacteria and algae have been specific substrata, owing to the effects of external conditions that in- widely reported and accepted. In one example, Phaeobacter gallaeciensis clude environmental changes (Hoštacká et al., 2010), competition with (a species of Roseobacter) is attracted to marine algae by producing other strains, and stimulation of algae on the substrata (Oliveira et al., auxin phenylacetic acid, which is a potent broad spectrum antibiotic 2015). As a result of diverse chemical and biological activities, the tropodithietic acid (TDA), and a valence tautomer thiotropocin of TDA

∗ Corresponding author. College of Environmental Science and Engineering, Ocean University of China, Qingdao, 266100, China. ∗∗ Corresponding author. Key Lab of Coastal Biology and Biological Resource Utilization, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264000, Shandong, China. E-mail addresses: [email protected] (J. Bai), [email protected] (S. Qin). 1 Co-ﬁrst authors. https://doi.org/10.1016/j.jenvman.2019.109459 Received 18 May 2019; Received in revised form 20 July 2019; Accepted 21 August 2019 Available online 31 August 2019 0301-4797/ © 2019 Elsevier Ltd. All rights reserved. J. Li, et al. Journal of Environmental Management 250 (2019) 109459

Fig. 1. Workﬂow of processes used in this study, including sample collection, data processing, analysis of community characteristics, and microorganism ecological function prediction. a. Sampled location and sampled reefs; samples were collected from reefs with brown algae (labeled as B), red algae (labeled as R), green algae (labeled as G) and without algae (labeled as NO). b. Characteristic analysis of community: alpha diversity analysis, community composition analysis, LEfSe analysis, beta diversity analysis, and evolutionary analysis. c. Microorganism ecological function prediction based on FAPROTAX database. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the Web version of this article.)

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(Geng et al., 2008; Thiel et al., 2010). In turn, the algae can contribute 2. Materials and methods nutrients and a suitable surface for the colonization of the Roseobacter (Buchan et al., 2005). Similarly, on coastal reef systems, bacterial 2.1. Sample collection biofilms can induce the attachment of aquatic eukaryotes, including algae, to form a complex symbiotic system between the algae and the Field sampling was conducted in a small area of no more than 25 bacteria (Amin et al., 2015; Ramanan et al., 2016; Koo et al., 2017). In square meters (37.92 °E, 120.76 °N) at the coast of Changdao Island. this system, algae benefit from the supply of nutrients (Makino et al., Samples were collected in triplicate from adjacent reefs settled with 2003; Wang et al., 2007), release of specific auxin (Le Bail et al., 2010; brown (Sargassum thunbergii; labeled as B), red (Gelidium; labeled as R), TAPIA et al., 2016; De Mesquita et al., 2019), inhibition of fouling green (Ulva lactuca L; labeled as G), or no (labeled as NO) algae in organisms (Rao et al., 2007; Egan et al., 2008), and prevention of August 2018 (Fig. 1A). The sampling environmental parameters were as harmful substances (Serra et al., 2010; Levy et al., 2011). In turn, algae follows: water depth of 0.5–1.5 m; salinity of 31.96; temperature of − improve the system environment by serving as a habitat for many 32.0 °C; conductivity of 47.21 mS cm 1. The bacterial biofilms were epibiont species, and also create substrata favoring the attachment of cautiously scratched with sterile scalpel blades, following the methods microorganisms and the production of many organic substances func- described by Pootakham et al. (2017). The collected microbiota were tioning as nutrients for bacterial multiplication and bacterial biofilm placed in 2-mL screw-capped tubes filled with sterile seawater and production (Singh et al., 2013). transported back to a vehicle within 2 h under low light inside a con- The interactions between algae and bacterial biofilm are not always tainer with a temperature of 4 °C. Upon returning to the laboratory, the beneficial. The abovementioned reciprocal relationships between the bacterial biofilm samples were stored at −20 °C for use in experiments rosebacter and algae can shift to a negative phase. Emiliania huxleyi (an to be conducted as soon as possible. alga) can generate p-coumaric acid (pCA) to indicate an elevated algal In the laboratory, after thawing, ultrasonic oscillation was promptly population density or algal senescence, and signal Phaeobacter gallae- applied to the centrifuge tubes containing various samples to remove ciensis (the Roseobacter species) to produce roseobacticides from phe- any impurities. Each separated seawater was filtered through a 0.22-μm nylacetic acid and a tropone precursor in TDA biosynthesis. This shift (47-mm) polycarbonate membrane and stored at −80 °C to conduct the from symbiosis to pathogenesis may allow P. gallaeciensis to access food DNA extraction experiments described below. sources from aging algae, and make the bacteria dissociate from dying algae and re-associate with other healthy algae (Seyedsayamdost et al., 2.2. DNA extraction, PCR, and sequencing 2011). Moreover, the lack of nutrients may lead to the deterioration of a reciprocal relationship, such as that wherein adhered bacteria and algae DNA was extracted using the Fast DNA SPIN Kit (MP BIO, USA) as compete with each other for phosphorus, when bacteria are limited by described by the manufacturer. Then, the Nano Drop 2000c spectro- the scarcity of phosphorus during the metabolic process of nutrients photometer (Thermo Fisher, USA) and agarose gel electrophoresis were (Wang et al., 2007). Moreover, pathogenic bacteria can exert disastrous used to determine the concentration and quality of the extracted DNA, effects on algae (Vairappan et al., 2008; Sun et al., 2012). Climatic which was subsequently purified using the methods specified in Ceh changes exert stress on marine habitat formers and their associated et al. (2011). To amplify the sample genes, the Polymerase Chain Re- microbiota, and produce an inflow of harmful pollutants. This dete- action (PCR) process was conducted according to the protocol of Yu riorates the environmental conditions and may make the bacterial et al. (2017). The primers 338 F (5′-ACTCCTACGGGAGGCAGCAG-3′) biofilms susceptible to potential opportunistic pathogens, which has a and 806 R (5′-GGACTACHVGGGTWTCTAAT-3′) flanking the V3–V4 negative effect on algae (Gachon et al., 2010). regions of the 16 S gene were used for environmental DNA amplifica- Changdao Island is located at the northeastern region of Shandong tion while attached with a unique 6-nt barcode at the end of the for- Province and is the largest island in North China (Chi et al., 2016). This ward primer. Using 20 ng of purified DNA as a template, the PCRs were area belongs to the East Asian monsoon climatic region and is char- carried out using the ABI GeneAmp 9700. In the PCR cycling, the DNA acterized by moderate rain, humid air, and mild climate. Owing to the was first pre-denatured at 95 °C for 5 min, and then again after 35 cycles rapid development of marine fisheries in Changdao Island, the urba- of denaturation at 94 °C for 30 s. After the denaturation had been nization process and economic level of the island have effectively im- completed, annealing was performed at 55 °C for 30 s, followed by ex- proved, whereas damages to the resources and the environment have tension at 72 °C for 40 s, and finally by extension at 72 °C for 7 min. become more extreme. For the purpose of ecological protection and The amplified products were combined and subsequently gene- sustainable development, since 2013, artificial reefs have been used to cleaned using the AxyPrep DNA Gel Extraction Kit (Axygen, USA). The promote the settlement of algae and exert fish-gathering effects (Wang resulting amplicon libraries were used for quantification through and Li, 2013). Under similar environmental conditions, various algae agarose gel electrophoresis and the QuantiFluor-ST fluorometer have settled onto various immersed reefs, but visible algae do not exist (Promega, USA). The Majorbio Co., Ltd. (Shanghai, China) 468-bp in some reefs, and this affects the reef's fish-gathering function. The PE300 Illumina MiSeq sequencing platform was used to perform high- underlying cause of this phenomenon has been inferred as the re- throughput sequencing for the PCR products. However, the B_2 sample lationship between the reef algae and the bacterial biofilms. However, was not successfully sequenced (the detailed processing methods used direct evidence clarifying the precise mechanism of these interactions is for the B_2 sample are described in S1). still ambiguous. Therefore, we investigated bacterial biofilms associated with algae-attached and algae-free reefs from Changdao Island 2.3. Data processing by carrying out diversity estimation and community composition analysis using high-throughput sequencing. The specific objectives of this The FastQC software was used to control the quality of the raw study were to investigate the community characteristics of bacterial FASTQ data obtained from the high-throughput sequencing products biofilms associated with various algal settlements on coastal reefs, ac- (Brown et al., 2017). Sequences shorter than 1000 nt were removed cess and compare the ecological functions of microbiota in the biofilms prior to downstream analyses based on the Quantitative Insights into using the FAPROTAX database, and link the compositions and functions Microbial Ecology (QIIME) pipeline, as described by Caporaso et al. of bacterial biofilms with the settlement of reefs by algae. (2010). Non-repetitive sequences from optimized sequence facilitates were extracted (Bokulich et al., 2013). Then, operational taxonomic unit (OTU) clustering was performed on the non-repetitive sequences (excluding single sequences) according to a similarity of 97%, and chimeras were removed during the clustering to obtain the

3 J. Li, et al. Journal of Environmental Management 250 (2019) 109459 representative OTU sequences (Edgar et al., 2011). All optimized se- Table 1 quences were mapped to the OTU representative sequence, and the Sample data statistics and alpha diversity analysis results. similarities of the representative sequence exceeding 97% were selected BRGNO to generate an OTU table (Caporaso et al., 2009). To obtain the taxonomic group information corresponding to each OTU, the Silva data- Number of sequences 54,507 47,688 49,194 43,157 base was used for comparison. Similarly, based on the Ribosomal Da- Goods coverage (%) 98.78 98.72 98.54 98.41 fi Pan OTU 1588 1486 1333 1241 tabase Project (RDP) pyrosequencing pipeline, a Bayesian classi cation Predicted OTU (Chao1) 1652 1421 1375 1263 algorithm was used to classify the 97% similarity level of the OTU re- Shannon diversity 5.69 5.43 4.91 4.80 presentative sequence and calculate the community composition of each sample at each taxonomic hierarchy (Desantis et al., 2006). The libraries belonging to non-bacteria taxa (Archaea, Chloroplast, and followed by the R-group samples and the G-group samples. Most bac- unassigned taxa), or accounting for < 0.01% of the total sequences, terial Shannon diversity indices associated with any of the B, R, and G were removed to ensure the validity of the bacterial community esti- groups (highest at HZ_1, 5.72) were also higher than those observed in mation (Bokulich et al., 2013). the NO group, with a range from 4.91 to 5.65 (Table 1). The ANOVA with a post-hoc test (Tukey) results revealed that the 2.4. Community characteristics and functional analysis Shannon and Chao index in different groups had various degrees of difference (Fig. S1). Significant Shannon index differences between The Mothur v.1.30.1 software package and the QIIME pipeline were groups B, R, and NO were detected (B–NO, p = 0.002; R–NO, used to analyze the alpha diversity, wherein the Chao1 estimator p = 0.009). Significant differences amongst groups B, R, and G were (predicted OTU) and Shannon diversity index were selected to evaluate also observed (B-G, p = 0.005; R-G, p = 0.024). Similarly, significant the richness and diversity of the community (Fig. 1B; Leray and differences in the Chao index were observed between B and NO Knowlton, 2016). Analysis of Variance (ANOVA) with a post-hoc test (p = 0.025). (Tueky) was conducted to detect whether the index values between multiple groups had any significant differences. Based on the taxonomic 3.3. Community composition analysis data sheet, the community distribution bar map of each sample and the Venn diagram at the OTU level were plotted using the R programming The B-group samples were dominated by ten phyla (using the class language (Pathak, 2014). Moreover, the vegan package in R was used to level for the Proteobacteria phylum): Alphaproteobacteria (31.6%), map the community heat map. The Circos-0.67-7 software was used to Bacteroidetes (29.5%), Gammaproteobacteria (12.8%), Cyanobacteria map a visual circle describing the correspondence between the samples (6.7%), Verrucomicrobia (3.5%), Actinobacteria (3.3%), and species (An et al., 2014; Krzywinski et al., 2009). Linear Dis- Deltaproteobacteria (2.9%), Parcubacteria (2.2%), Fusobacteria criminant Analysis Effect Size (LEfSe) analysis was carried out, and the (1.5%), and Firmicutes (1.4%). Approximately 96.0% of bacterial se- results are presented in visual graphs (Segata et al., 2011). The QIIME quences in the R group could be classified into twelve phyla: pipeline and R language were used to calculate the beta diversity dis- Alphaproteobacteria (35.7%), Bacteroidetes (22.0%), tance matrix, and draw the hierarchical clustering tree and principal co- Gammaproteobacteria (12.0%), Fusobacteria (8.0%), Actinobacteria ordinate analysis (PCoA) statistical map. According to the maximum (5.8%), Verrucomicrobia (3.2%), Deltaproteobacteria (2.2%), likelihood method, the phylogenetic tree was constructed by selecting Cyanobacteria (2.0%), Saccharibacteria (1.9%), Deinococcus-Thermus sequences corresponding to the classification information at a certain (1.2%), Parcubacteria (1.1%), and Firmicutes (1.0%). Eight phyla ac- hierarchy using the FigTree v1.4.3 software. The sequencing data were counted for more than 1% in the G group: Alphaproteobacteria functionally annotated using the FAPROTAX database (Louca et al., (53.8%), Bacteroidetes (20.6%), Cyanobacteria (7.8%), 2016). The results are presented as graphs created using the Permut- Gammaproteobacteria (6.4%), Fusobacteria (3.6%), Matrix software (Fig. 1C). Deltaproteobacteria (1.6%), Verrucomicrobia (1.4%), and Actinobacteria (1.3%). In the NO group, 97% of the bacterial sequences 2.5. Data availability could be classified into six phyla: Alphaproteobacteria (32.7%), Cyanobacteria (26.6%), Bacteroidetes (22.2%), Fusobacteria (8.4%), The sequence data of this study were deposited to the Sequence Gammaproteobacteria (6.2%), and Deltaproteobacteria (1.3%). The Read Archive of NCBI (https://www.ncbi.nlm.nih.gov/). A bio-project abundant phyla/classes could cluster all groups into two parts: one part associated with this study was applied for and processed in NCBI with for the NO group and another part for the algae-attached groups (B, R, the accession number PRJNA532757. The metatranscriptome se- and G), which indicates two distinctive distances of microbial com- quences for all 11 samples were stored in a sequence reading file with munities (Fig. 2; Fig. S2). accession number SRR9705613-SRR9705623. 3.4. Community LEfSe analysis 3. Results The LEfSe can analyze differences in the species composition be- 3.1. Sample information statistics tween groups and identify different microbial species (http:// huttenhower.sph.harvard.edu/galaxy/). The LDA results (Fig. 3; Table The PCR products of the 16 S rRNA gene's V3–V4 region were se- S1) revealed that the B group was discriminately associated with the quenced. Hence, the barcoded high-throughput sequencing generated phylum Chlorobi (including class Chlorobia, order Chlorobiales and 529,132 quality sequences from 11 samples, with an average of 48,103 family OPB56), Firmicutes (including class Firmicutes bacilli), Parcu- sequences per sample (after optimization; Table 1). bacteria, Planctomycetes (including class OM190, order Phyci- sphaerales, family Phycisphaeraceae), class Flavobacteriia (including 3.2. Alpha diversity analysis order Flavobacteriales, family Flavobacteriaceae, genera Lutimona, Eu- doraea, Aquibacter, Actibacter, and Algibacter, and species Algibacter Only the denoised sequences of the QIIME analyses are discussed in aestuarii), Deltaproteobacteria, order Caldilineales (including family this paper. The Chao index (predicted OTUs) for each sample in groups Caldilineaceae), Xanthomonadales, families Ferrimonadaceae (in- B, R, and G ranged from 1375 to 1652, which is higher than that in the cluding genus Ferrimonas and species Ferrimonas pelagia), Cellvi- NO group (1263). The B-group samples had the highest Chao index, brionaceae, Halieaceae (including genus Haliea and the OM60/NOR5

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Fig. 2. Community heat map showing the relative abundance of predominant phyla/classes using color legend. These dominant bacteria taxa clustered the groups into two distinct distances. The Proteobacteria phyla are shown at class level. Samples collected from reefs with brown algae were labeled as B; samples with red algae were labeled as R; samples with green algae were labeled as G; samples without algae were labeled as NO. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the Web version of this article.)

clade), Rhodospirillaceae, and genera Hirschia and Marivita. The discriminative taxa related to the R group were phyla Gracilibacteria, Actinobacteria (including class Actinobacteria order Acidimicrobiales), Saccharibacteria, classes Clostridia (including order Halanaerobiales), and Gammaproteobacteria (including order Chromatiales, family Granulosicoccaceae, genera Granulosicoccus, Coxiella, and Thiothrix), orders Rhodospirillales and Desulfobacterales (including family De- sulfobulbaceae), family Helicobacterace (including genus Sulfurovum), genera Portibacter, Limnobacter, Ahrensia, Oricola, Litorimonas, and Hellea, and species Aquisalinus ﬂavus. Discriminative taxa associated with the G group were relatively sparse, and only included class Anaerolineae (including order Anaerolineales and family Anaerolinea- ceae), and genera Ulvibacter, Winogradskyella, Croceitalea, Sphingomi- crobium, Tropicimonas, Loktanella, and Boseongicola. The discriminative taxa associated with the NO group were phylum Cyanobacteria (including class member Cyanobacteria, order member Subsection I and Subsection III, Family I of Subsection I, and Family I of Subsection III, Fig. 4. Principal co-ordinate analysis results showing the spatial variations of and genus Phormidium), unclassiﬁed Bacteroidetes, order Bradymona- four groups according to the weighted UniFrac distance. The top two PCoA axes dales, family Shewanellaceae (including genus Shewanella), genus Ru- (PC1 and PC2) are shown in the graph. Samples collected from reefs with brown bidimonas, species Lewinella agrilytica, Nonlabens sediminis, Tenaciba- algae were labeled as B; samples with red algae were labeled as R; samples with culum skagerrakense, Vibrio mediterranei, and Pseudoalteromonas green algae were labeled as G; samples without algae were labeled as NO. ruthenica. of microbial communities (Fig. 4). In the coordinates of PC1 and PC2, 3.5. Beta diversity analysis the PC1 and PC2 axis explains 47.27% and 24.24% of the total variation. The samples of the NO group are dispersed on the right side of the The principal co-ordinate analysis of the weighted UniFrac distance graph, along the primary axis and away from the B, R, and G groups. On revealed that the B, R, G, and NO groups possessed distinctive distances the left side of the coordinates, the samples of the B and R groups were

Fig. 3. Taxonomic cladograms showing significant bacterial taxa discriminated in B, R, G, and NO groups. Yellow circles indicate non-significant taxa and circle diameters indicate the relative abundance of each taxon. Abs LDA score > 3.0. Samples collected from reefs with brown algae were labeled as B; samples with red algae were labeled as R; samples with green algae were labeled as G; samples without algae were labeled as NO. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

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Fig. 5. Heat map of classiﬁable bacterial metabolisms in all four groups. Samples collected from reefs with brown algae were labeled as B; samples with red algae were labeled as R; samples with green algae were labeled as G; samples without algae were labeled as NO. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the Web version of this article.)

interlaced and separated from the clustered G group. Brieﬂy, the phototrophs, the communities in all groups were dominated by the communities on reefs with identical algae settlements were relatively groups most closely related to known heterotrophs. However, the per- clustered together and separated from those on reefs without algae. centage in the NO group declined, while the B, R, and G groups reached Overall, the top two PCoA axes explain 71.5% of the variation in the 96.78%, and the NO group reached 82.51%. The bacterial communities diﬀerent communities. belonging to the NO group contained more groups related to photo- autotrophs (17.48%).

3.6. Prediction of microorganism's ecological function 4. Discussion FAPROTAX was used to map prokaryotic taxa (e.g., genus and species) to metabolic or other ecologically relevant functions (Louca This study investigated the surface of reefs in Changdao Island and et al., 2016). The bacterial taxa were categorized into 54 types, each found that they harbored abundant and diverse microbial communities with different ecological functions (total of 90 types in the database). with specific characteristics. Environmental parameters such as tem- The functions of annotated taxa were related to the metabolism of C perature, salinity, and electrical conductivity were measured within a (methylotrophy, methanotrophy, chitinolysis, cellulolysis, and xylano- sampling area of 25 square meters. However, the difference of hydrolysis), N (aerobic ammonia oxidation, nitrate respiration, and deni- logical conditions and physical and chemical parameters was much trification), S (dark sulfide oxidation, sulfite respiration, and respiration smaller than the diurnal variation and tidal range variation of the sta- of sulfur compounds), and other trace elements (oxidation and re- tion itself. For this result, we simplified the abovementioned parameters spiration of iron and manganese). The relative abundance of each to better investigate the structure and function of bacteria associated function was processed to generate the bacterial metabolic heat map with different algae and establish the relationship between them. (Fig. 5), which clearly illustrates the diverse ecological functions and Eleven communities from different reefs were clustered into two cate- metabolic pathways in each group. The richer diversity of the ecolo- gories: the first category corresponds to the B, R, and G groups, while gical functions and metabolic types is associated with the B, R, and G the second one corresponds to the NO group. This indicates a separation groups (40 function types existed in the R group, 45 function types between the bacterial bio films with and without algal symbiosis. The existed in the B group, and 41 function types existed in the G group), alpha diversity indices for each of the B, R, and G groups (the Chao rather than with the NO group (only 35 function types were present). index ranged from 1375 to 1652, and the Shannon diversity index The percentage of microbiota associated with carbon metabolisms ranged from 4.91 to 5.69) were higher than those of the NO group (the was more than 90% amongst all groups (Fig. 6A). A certain percentage Chao index was 1263, and the Shannon diversity index was 4.80). An of sulfur-metabolism-related communities existed in all groups. The B assay focusing on the microbial diversity on benthic reefs produced and R groups had the highest proportion, followed by the G group and similar results, wherein the diversity of microbial communities asso- NO group, which had the lowest proportion. The proportion of classi- ciated with the reef algae (the Chao index was 266–461, and the fiable bacteria associated with the metabolism of nitrogen was rela- Shannon diversity index was 2.84–5.63) was richer than that associated tively constant in all groups. The taxa related to the metabolic processes with the reef-building coral (the Chao index was 953–3300, and the of trace elements (iron and manganese) had low abundance in all Shannon diversity index was 6.22–7.82; Barott et al., 2011). This ten- groups (less than 1%). Additionally, bacteria related to the metabolism dency indicates that more diverse functional microbiota can coexist of certain trace elements were only observed in specific groups. with algae, and thus produce more complex reactions in the algae- All functional annotated bacteria were classified as aerobic, fa- bacterial symbiotic system. cultative, or anaerobic. Additionally, it was found that the bacterial Discriminative taxa were also found amongst the four groups, and libraries in the B, R, G, and NO groups were dominated by sequences their detailed descriptions were presented in Section 3.4. This varia- that were most similar to aerobes. However, the percentage in the NO bility of bacterial communities between the four groups was likely group declined, and the percentage in the B, R, G, NO groups was caused by the diverse heterogeneous assemblage of algae and bacteria, 67.76%, 70.20%, 74.47%, and 52.04%, respectively, as shown in which increased the heterogeneity of bacterial communities. Some of Fig. 6B. Moreover, the percentage of bacteria related to the facultative these heterogeneous bacteria are widely distributed in other habitats class was highest in the NO group (41.11%) and lowest in the R group such as extensive sea water (Roush et al., 2014), tidal flat sediment (12.09%). The percentage of aerobic bacteria in the R group was the (Kim et al., 2008), marine organisms (Hyun et al., 2015), and even highest amongst all groups (17.71%), while the B, G, and NO groups industrial production (Roush et al., 2014). However, an association were not very different (~8%). With regard to heterotrophs and with algae has been demonstrated for most of these bacteria, which

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Fig. 6. Relative abundance of classifiable bacterial metabolisms related to reefs with or without various algae: a. pie chart of microbial composition associated with the metabolism of different nutrients; b. Histogram of microbial composition related to oxygen metabolism (top) and histogram of microbial composition related to carbon metabolism (bottom). Samples collected from reefs with brown algae were labeled as B; samples with red algae were labeled as R; samples with green algae were labeled as G; samples without algae were labeled as NO. suggests that the bacteria engage in multiple interactions with algae. variety of isoprenoids. Consequently, Saccharibacteria can generate The biofilms on the surface of the kelp Laminaria hyperborea exhibit a acetate and lactate by fermenting the algal exudates and tissues to higher proportion of Planctomycetes compared with other investigated promote the carbon cycle in the system (Starr et al., 2018). Moreover, Planctomycete-rich habitats (open water, peat bogs, and sandy sedi- Anaerolineaceae have been found in the G group, which indicates the ments; Bengtsson and Øvreås, 2010). A study on bacterial communities existence of fermentation and the oxidation of alkanes to small mole- associated with the genus Asparagopsis (red seaweed) also found a high cules such as formate, acetate, hydrogen, and carbon dioxide (Liang abundance of Acidimicrobiales in Asparagopsis armata samples (Aires et al., 2015). et al., 2016). Additionally, most species in the Algibacter genus (Fla- Carbon enrichment in the surrounding environment is considered to vobacteria) were isolated from or were close to the algae habitat, which promote the settlement of opportunistic algae, while the types of settled indicates a preference for complex algae polysaccharides (Sun et al., algae may be related to the ecological cycle and sulfur supply. The 2016). The adherence of these heterogeneous bacteria on coastal reefs percentage of classifiable bacteria associated with sulfur metabolism may improve the surrounding environment through various nutrient was high on reefs with attached algae, particularly in the B and R metabolic and specific reactions to satisfy the requirements of algae. groups where it reached up to 3.57% and 5.63%, respectively (Fig. 6A). Thus, a settlement of opportunistic algae can be attracted to reefs. This conclusion is based on the distinct physiological characteristics of Furthermore, various bacteria can protect the algae from adverse ex- these algal groups. Brown and red algae can release sulfur-containing ternal factors, and thereby maintain the steady state of the algal sym- secretions (elicitors) when subjected to abiotic or biotic stress with biosis system and promote the healthy development of algae. The intense sunlight, wind, or bacterial and viral infections (Hou et al., FAPROTAX results revealed that, in all groups, the communities were 2015). Red coralline algae are macroalgal producers of dimethylsul- dominated by the bacteria most related to carbon metabolism (greater phoniopropionate (DMSP), which is a vital component of the marine than 93%). This proves that the metabolic activities of carbon are ex- sulfur cycle (Sunda et al., 2002). Porphyran, which is a sulfated ga- tensive on reef surfaces. This microbial carbon metabolism can main- lactan, is the main cellular polysaccharide in marine red alga. Oligo- tain the stability of the carbon cycle in the environment, which is the porphyrans obtained by the acid hydrolysis of porphyrin use their basis for algal attachment. Moreover, compared with the NO group, the H2O2-inducing abilities as defense responses to Pyropia yezoensis (Hou settlement of algae in the B, R, and G groups leads to a complex ex- et al., 2015). Moreover, various algal tissues may contain a sulfo- change of carbon elements between the algae and bacteria. With the compound. For example, fucoidan (polysaccharides containing a sub- settlement of algae on the reef surface, the algae become primary stantial amount of sulfate ester groups) has been reported as a con- carbon producers through the discharge of carbon and tissue growth. stituent of brown seaweed (Bilan et al., 2002) and possesses various Additionally, through the absorption of exuded carbon and the de- biological properties, such as anticoagulant, antithrombotic, and anti- gradation of necrotic tissues, bacterial biofilms convert these carbo- viral properties (Li et al., 2008). Planctomycetes (found in the B group) naceous compounds to specific forms that can be reused by the algae. can particularly degrade sulfated polymeric carbon, as proven by the The various bacteria with carbon-metabolizing functions found on the detection of genes involved in the breakdown of sulfated poly- investigated reefs provide insight to these processes. Marine Flavo- saccharides (Glöckner et al., 2003). Thiothrix are colorless sulfur-oxi- bacteriia (discriminative taxa in the B group) play an important role in dizing bacteria that may deposit sulfur when grown in the presence of the degradation of algal tissues owing to the use of biopolymers such as sulphide or thiosulphate (Nielsen et al., 2000). These sulfur-oxidizing polysaccharides and proteins (Thomas et al., 2012). The Sacchar- and sulfur-metabolizing bacteria cannot only metabolize sulfur-con- ibacteria found in the R group are capable of degrading cellulose, taining substances in the environment, but can also decompose residual hemicellulose, pectin, starch, and 1,3-β-glucan. Additionally, they can sulfur-containing secretions or corroded algal tissues to generate ab- generate hydrolase to breakdown salicylic acid and interconvert a sorbable sulfur molecules, which are consumed again by these algae.

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This study found that the inter-group specificity of bacteria is as- 5. Conclusions sociated with other trace elements, which may also explain the types of settled algae (Fig. 5). Geodermatophilus (Actinobacteria), which is a type Coastal reefs with and without attached algae harbor abundant and of bacteria associated with manganese oxidation, have only been found characteristic microbial communities. Groups B, R, G, and NO have in the G group. Additionally, iron-associated bacteria have only been significant differences in terms of microbial community structures and discovered in groups with attached algae. For instance, Ferrimonas ecological functions. The characteristic microbiota related to the B, R, (found in the B group) are reducing bacteria that can use yeast extract, and G groups have richer diversity compared with those found in the lactate, pyruvate, casamino acids, and tryptone as electron donors, and NO group. The discriminative taxa in the B group are mostly classified carbon sources to reduce iron(III) oxyhydroxide, iron(III) citrate, sele- into the Planctomycetes, Parcubacteria, Firmicutes, and Chlorobi phyla, nate, arsenate, elemental sulfur, and thiosulfate (Nakagawa et al., and the Flavobacteria and Deltaproteobacteria classes. Additionally, the 2006). bacteria in the R group are mostly associated with the Gracilibacteria Furthermore, on reefs with algal settlement, various taxa have been and Actinobacteria phyla, and the Gammaproteobacteria, observed to exert protective effects. Acidimicrobiales discriminately Deltaproteobacteria, and Clostridia classes. Although discriminative associate with the R group, and various studies have demonstrated that taxa were discovered in other phyla or classes, the most relevant bac- these bacteria can contribute to the resistance of oxidative stress and teria in the G group belong to the Anaerolineae class. The NO group toxic compounds (heavy metal detoxification; Aires et al., 2016). The mainly harbors bacteria belonging to the Cyanobacteria phylum, and toxic effects of heavy metals and other environmental stresses to algae unclassified Bacteroidetes. Based on the comparative analysis of com- are produced by reactive oxygen species (ROS), while algae respond to munity characteristics and the ecological functions of bacterial biofilms these toxic compounds by producing antioxidants such as glutaredoxins in the four groups, it was concluded that the metabolism and supply of and glutathione. The bacteria effects supporting the resistance of toxic nutrients by the bacterial biofilms induced the settlement of opportu- compounds are associated with the synthesis pathway of glutathione, nistic algae. Particularly, the presence of bacteria associated with sulfur which is used to scavenge the produced ROS (Dring, 2005; Mellado and other elements may explain the settlement of different algae types et al., 2012). Various Haliea (Gammaproteobacteria, found in the B on reefs. Furthermore, in groups with algal attachment, various dis- group) can generate alkene monooxygenases to oxidize alkenes, which criminative taxa were observed to exert protective effects, including has multiple effects on algae, such as the inducement of chlorophyll-a resistance to toxic substances in the environment and prevention loss and the aggravation of mastoparan-induced cell death (Suzuki against pathogenic bacterial invasion. This was essential to maintain et al., 2012). Similarly, a few bacteria have been observed to synthesize the steady state of the algae-bacteria symbiotic environment and pro- a diverse array of sterols and cyclic triterpenoids with defensive func- mote the healthy development of algae settlements on reefs. tions against pests and pathogens. For example, a species of Lutimonas Additionally, for the NO group, the competition of photosynthetic (Flavobacteria, found in the B group) can produce two isoarborinol-like bacteria for light and nutrients and the toxicity of pathogenic bacteria lipids, eudoraenol, and adriaticol (Banta et al., 2017). This resistance to such as Pseudoalteromonas can explain the lack of algal settlements in toxic substances in the environment and the prevention of pathogenic the NO group. bacterial invasion are essential for maintaining the steady state of the Therefore, in practical artificial reef applications, microbial agents algae-bacteria symbiotic environment and promoting the healthy de- of bacteria beneficial to the nutrient supply can be introduced to reefs velopment of algae settled on reefs. to attract the settlement of opportunistic algae. Additionally, the at- In contrast, besides the lack of relevant metabolic bacteria, the traction of specific types of algal attachment should focus on bacteria absence of algal settlements in the NO group is attributed to the inva- associated with special elements such as sulfur and trace elements. sion of pathogenic and competitive bacteria and the lack of associated Moreover, on artificial reefs, phototrophic bacteria (Cyanobacteria) and protective microbiota. Pseudoalteromonas has been observed to be pa- pathogenic bacteria (Pseudoalteromonas) should be eradicated to thogenic in group NO. The swarming of Pseudoalteromonas has potent maintain the benign development of algae. The influence of various algicidal effects, which can cause rapid cell lysis and the death of temporal and spatial factors should be considered, and the sample size gymnodinoids (including Gymnodinium catenatum) and raphidophytes should be increased to further strengthen the representativeness of this (including Heterosigma akashiwo and Chattonella marina), and the study. However, according to the results, on reefs with different types of ecdysis of armored dinoflagellates (such as Alexandrium catenella) attached algae, it is possible to isolate discriminative bacteria and then (Lovejoy et al., 1998). Pseudoalteromonas have pronounced effects apply them to the settlement and development of algae on artificial against the germination of spores from green alga Ulva lactuca and red reefs, which will be investigated in future work. alga Polysiphonia through the production of an extracellular component with a specific activity toward algal spores (Egan et al., 2001). Ad- Acknowledgements ditionally, compared with the B, R, and G groups, discriminative taxa associated with the NO group mostly belong to the phylum of Cyano- This study was financially supported by the Science and Technology bacteria, which are widely considered as oxygenic photosynthetic program of Yantai (No. 2017ZH090 and No. 2016YTZD0007). We bacteria (Soo et al., 2017). These results correspond to the FAPROTAX would like to thank Yong Wang and Longchuan Zhuang for their help results wherein the proportion of bacteria associated with photo- with field sampling. We also thank Zhengyi Liu for his help in identi- autotrophs in the NO group reached 17.48%, which is the highest fying attached algae. We extend our gratitude to the journal reviewers proportion amongst all groups (Fig. 6B). However, owing to the com- for their comments and suggestions, which helped in significantly im- petition for light or other phototrophic substances, a higher proportion proving the manuscript. Finally, we thank Professor Yangguo Zhao for of phototrophs may be detrimental to the attachment of algae. More- his help in revising the manuscript. over, algae have been observed to exert allelochemical effects through secretions of antimicrobial metabolites targeting photosynthetic bac- Appendix A. Supplementary data teria to prevent the photosynthetic epibionts from competing with macroalgae for light and nutrients (Beam et al., 2016). Owing to the Supplementary data to this article can be found online at https:// allelochemical effects of algae on phototrophic bacteria, the relation- doi.org/10.1016/j.jenvman.2019.109459. ship between them is considered as antagonistic. Furthermore, the breeding of over-dense cyanobacteria can produce inherent cyanotoxins References (including cyclic peptides and alkaloids) in toxic quantities in the vi- cinity of hydrophytes and fishes (Van Apeldoorn et al., 2007). Aires, T., Serrão, E.A., Engelen, A.H., 2016. Host and environmental specificity in

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bacterial communities associated to two highly invasive marine species (genus agents. Sci. Rep. 7, 6908. Asparagopsis). Front. Microbiol. 7, 559. Krzywinski, M., Schein, J., Birol, İ., Connors, J., Gascoyne, R., Horsman, D., Jones, S.J., Amin, S.A., Hmelo, L.R., Van Tol, H.M., Durham, B.P., Carlson, L.T., Heal, K.R., Morales, Marra, M.A., 2009. Circos: an information aesthetic for comparative genomics. R.L., Berthiaume, C.T., Parker, M.S., Djunaedi, B., Ingalls, A.E., Parsek, M.R., Moran, Genome Res. 19, 1639–1645. M.A., Armbrust, E.V., 2015. Interaction and signalling between a cosmopolitan Le Bail, A., Billoud, B., Kowalczyk, N., Kowalczyk, M., Gicquel, M., Le Panse, S., Stewart, phytoplankton and associated bacteria. Nature 522, 98–101. S., Scornet, D., Cock, J.M., Ljung, K., Charrier, B., 2010. Auxin metabolism and An, J., Lai, J., Sajjanhar, A., Batra, J., Wang, C., Nelson, C.C., 2014. J-Circos: an inter- function in the multicellular brown alga Ectocarpus siliculosus. Plant Physiol. 153, active Circos plotter. Bioinformatics 31, 1463–1465. 128–144. Banta, A.B., Wei, J.H., Gill, C.C., Giner, J.L., Welander, P.V., 2017. Synthesis of arborane Leray, M., Knowlton, N., 2016. Visualizing patterns of marine eukaryotic diversity from triterpenols by a bacterial oxidosqualene cyclase. Proc. Natl. Acad. Sci. 114, 245–250. metabarcoding data using QIIME. Methods Mol. Biol. 1452, 219–235. Barott, K.L., Rodriguez-Brito, B., Janouškovec, J., Marhaver, K.L., Smith, J.E., Keeling, P., Levy, J.L., Stauber, J.L., Wakelin, S.A., Jolley, D.F., 2011. The effect of field-collected Rohwer, F.L., 2011. Microbial diversity associated with four functionaG groups of biofilms on the toxicity of copper to a marine microalga (Tetraselmis sp.) in laboratory benthic reef algae and the reef-building coral Montastraea annularis. Environ. bioassays. Mar. Freshw. Res. 62, 1362–1372. Microbiol. 13, 1192–1204. Li, B., Lu, F., Wei, X., Zhao, R., 2008. Fucoidan: structure and bioactivity. Molecules 13, Beam, J.P., Jay, Z.J., Schmid, M.C., Rusch, D.B., Romine, M.F., Jennings, R.D.M., 1671–1695. Kozubal, M.A., Tringe, S.G., Wagner, M., Inskeep, W.P., 2016. Ecophysiology of an Liang, B., Wang, L.-Y., Mbadinga, S.M., Liu, J.F., Yang, S.Z., Gu, J.D., Mu, B.Z., 2015. uncultivated lineage of Aigarchaeota from an oxic, hot spring filamentous ‘streamer’ Anaerolineaceae and Methanosaeta turned to be the dominant microorganisms in al- community. ISME J. 10, 210–224. kanes-dependent methanogenic culture after long-term of incubation. Amb. Express Bengtsson, M.M., Øvreås, L., 2010. Planctomycetes dominate biofilms on surfaces of the 5, 37. kelp Laminaria hyperborea. BMC Microbiol. 10, 261. Louca, S., Parfrey, L.W., Doebeli, M., 2016. Decoupling function and taxonomy in the Bilan, M.I., Grachev, A.A., Ustuzhanina, N.E., Shashkov, A.S., Nifantiev, N.E., Usov, A.I., global ocean microbiome. Science 353, 1272. 2002. Structure of a fucoidan from the brown seaweed Fucus evanescens C.Ag. Lovejoy, C., Bowman, J.P., Hallegraeff, G.M., 1998. Algicidal effects of a novel marine Carbohydr. Res. 337, 719–730. Pseudoalteromonas isolate (Class Proteobacteria, Gamma Subdivision) on harmful algal Bokulich, N.A., Subramanian, S., Faith, J.J., Gevers, D., Gordon, J.I., Knight, R., Mills, bloom species of the genera Chattonella, Gymnodinium, and Heterosigma. Appl. D.A., Caporaso, J.G., 2013. Quality-filtering vastly improves diversity estimates from Environ. Microbiol. 64, 2806–2813. Illumina amplicon sequencing. Nat. Methods 10, 57–59. Makino, W., Cotner, J.B., Sterner, R.W., Elser, J.J., 2003. Are bacteria more like plants or Brown, J., Pirrung, M., Mccue, L.A., 2017. FQC Dashboard: integrates FastQC results into animals? Growth rate and resource dependence of bacterial C: N: P stoichiometry. a web-based, interactive, and extensible FASTQ quality control tool. Funct. Ecol. 17, 121–130. Bioinformatics 33. Mellado, M., Contreras, R.A., Gonz Lez, A., Dennett, G., Moenne, A., 2012. Copper-in- Buchan, A., González, J.M., Moran, M.A., 2005. Overview of the marine Roseobacter duced synthesis of ascorbate, glutathione and phytochelatins in the marine alga Ulva lineage. Appl. Environ. Microbiol. 71, 5665–5677. compressa (Chlorophyta). Plant Physiol. Biochem. 51, 102–108. Butturini, A., Battin, T.J., Sabater, F., 2000. Nitrification in stream sediment biofilms: the Nakagawa, T., Iino, T., Suzuki, K.-I., Harayama, S., 2006. Ferrimonas futtsuensis sp. nov. role of ammonium concentration and DOC quality. Water Res. 34, 629–639. and Ferrimonas kyonanensis sp. nov., selenate-reducing bacteria belonging to the Caporaso, J.G., Bittinger, K., Bushman, F.D., Desantis, T.Z., Andersen, G.L., Knight, R., Gammaproteobacteria isolated from Tokyo Bay. Int. J. Syst. Evol. Microbiol. 56, 2009. PyNAST: a flexible tool for aligning sequences to a template alignment. 2639–2645. Bioinformatics 26, 266–267. Nielsen, P.H., De Muro, M.A., Nielsen, J.L., 2000. Studies on the in situ physiology of Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Thiothrix spp. present in activated sludge. Environ. Microbiol. 2, 389–398. Fierer, N., Pe, A., G, A., Goodrich, J.K., Gordon, J.I., 2010. QIIME allows analysis of Oliveira, N.M., Martinez-Garcia, E., Xavier, J., Durham, W.M., Kolter, R., Kim, W., Foster, high-throughput community sequencing data. Nat. Methods 7, 335–336. K.R., 2015. Biofilm formation as a response to ecological competition. PLoS Biol. 13, Ceh, J., Van keulen, M., Bourne, D.G., 2011. Coral-associated bacterial communities on e1002191. ningaloo reef, western Australia. FEMS Microbiol. Ecol. 75, 134–144. Pathak, M.A., 2014. Overview of the R programming language. In: Beginning Data Chi, Y., Shi, H., Wang, X., Qin, X., Zheng, W., Peng, S., 2016. Impact factors identification Science with R. Springer, Cham, pp. 5–17. of spatial heterogeneity of herbaceous plant diversity on five southern islands of Pootakham, W., Mhuantong, W., Yoocha, T., Putchim, L., Sonthirod, C., Naktang, C., Miaodao Archipelago in North China. Chin. J. Oceanol. Limnol. 34, 937–951. Thongtham, N., Tangphatsornruang, S., 2017. High resolution profiling of coral-as- De Mesquita, M.M.F., Crapez, M.A.C., Teixeira, V.L., Cavalcanti, D.N., 2019. Potential sociated bacterial communities using full-length 16S rRNA sequence data from interactions bacteria-brown algae. J. Appl. Phycol. 31–867. PacBio SMRT sequencing system. Sci. Rep. 7, 2774. Desantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Keller, K., Huber, T., Dalevi, D., Hu, Ramanan, R., Kim, B.H., Cho, D.H., Oh, H.M., Kim, H.S., 2016. Algae–bacteria interac- P., Andersen, G.L., 2006. Greengenes: chimera-checked 16S rRNA gene database and tions: evolution, ecology and emerging applications. Biotechnol. Adv. 34, 14–29. workbenchcompatible in ARB. Appl. Environ. Microbiol. 72, 5069–5072. Rao, D., Webb, J.S., Holmstr, M.C., Case, R., Low, A., Steinberg, P., Kjelleberg, S., 2007. Dring, M.J., 2005. Stress resistance and disease resistance in seaweeds: the role of reactive Low densities of epiphytic bacteria from the marine alga Ulva australis inhibit set- oxygen metabolism. Adv. Bot. Res. 43, 175–207. tlement of fouling organisms. Appl. Environ. Microbiol. 73, 7844–7852. Edgar, R.C., Haas, B.J., Clemente, J.C., Quince, C., Knight, R., 2011. UCHIME improves Roush, D.W., Elias, D.A., Mormile, M., 2014. Metabolic capabilities of the members of the sensitivity and speed of chimera detection. Bioinformatics 27, 2194. order Halanaerobiales and their potential biotechnological applications. Curr. Egan, S., James, S., Holmström, C., Kjelleberg, S., 2001. Inhibition of algal spore ger- Biotechnol. 3, 3–9. mination by the marine bacterium Pseudoalteromonas tunicata. FEMS Microbiol. Ecol. Segata, N., Izard, J., Waldron, L., Gevers, D., Miropolsky, L., Garrett, W.S., Huttenhower, 35, 67–73. C., 2011. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60. Egan, S., Thomas, T., Kjelleberg, S., 2008. Unlocking the diversity and biotechnological Serra, A., Guasch, H., Admiraal, W., Geest, H.G.V.D., Van Beusekom, S.A.M., 2010. potential of marine surface associated microbial communities. Curr. Opin. Microbiol. Influence of phosphorus on copper sensitivity of fluvial periphyton: the role of che- 11, 219–225. mical, physiological and community-related factors. Ecotoxicology 19, 770–780. Gachon, C.M., Sime-Ngando, T., Strittmatter, M., Chambouvet, A., Kim, G.H., 2010. Algal Seyedsayamdost, M.R., Case, R.J., Kolter, R., Clardy, J., 2011. The Jekyll-and-Hyde diseases: spotlight on a black box. Trends Plant Sci. 15, 633–640. chemistry of Phaeobacter gallaeciensis. Nat. Chem. 3, 331. Geng, H., Bruhn, J.B., Nielsen, K.F., Gram, L., Belas, R., 2008. Genetic dissection of tro- Singh, R.P., Shukla, M.K., Mishra, A., Reddy, C., Jha, B., 2013. Bacterial extracellular podithietic acid biosynthesis by marine roseobacters. Appl. Environ. Microbiol. 74, polymeric substances and their effect on settlement of zoospore of Ulva fasciata. 1535–1545. Colloids Surfaces B Biointerfaces 103, 223–230. Glöckner, F.O., Kube, M., Bauer, M., Teeling, H., Lombardot, T., Ludwig, W., Gade, D., Soo, R.M., Hemp, J., Parks, D.H., Fischer, W.W., Hugenholtz, P., 2017. On the origins of Beck, A., Borzym, K., Heitmann, K., 2003. Complete genome sequence of the marine oxygenic photosynthesis and aerobic respiration in Cyanobacteria. Science 355, planctomycete Pirellula sp. strain 1. Proc. Natl. Acad. Sci. 100, 8298–8303. 1436–1440. Gutierrez-Pacheco, M.M., Gonzalez-Aguilar, G.A., Martinez-Tellez, M.A., Lizardi- Starr, E.P., Shi, S., Blazewicz, S.J., Probst, A.J., Herman, D.J., Firestone, M.K., Banfield, Mendoza, J., Madera-Santana, T.J., Bernal-Mercado, A.T., Vazquez-Armenta, F., J.F., 2018. Stable isotope informed genome-resolved metagenomics reveals that Ayala-Zavala, J.F., 2018. Carvacrol inhibits biofilm formation and production of Saccharibacteria utilize microbially-processed plant-derived carbon. Microbiome 6, extracellular polymeric substances of Pectobacterium carotovorum subsp. carotovorum. 122. Food Control 89, 210–218. Sun, X., He, Y., Xu, N., Xia, Y., Liu, Z., 2012. Isolation and identification of two strains of Hoštacká, A., Čižnár, I., Štefkovičová, M., 2010. Temperature and pH affect the produc- pathogenic bacteria and their effects on the volatile metabolites of Gracilariopsis le- tion of bacterial biofilm. Folia Microbiol. 55, 75–78. maneiformis (Rhodophyta). J. Appl. Phycol. 24, 277–284. Hou, Y., Wang, J., Simerly, T., Jin, W., Zhang, H., Zhang, Q., 2015. Hydrogen peroxide Sun, C., Fu, G.Y., Zhang, C.Y., Hu, J., Xu, L., Wang, R.J., Su, Y., Han, S.B., Yu, X.Y., Cheng, released from Pyropia yezoensis induced by oligo-porphyrans: mechanisms and effect. H., Zhang, X.Q., Huo, Y.Y., Xu, X.W., Wu, M., 2016. Isolation and complete genome J. Appl. Phycol. 27, 1639–1649. sequence of Algibacter alginolytica sp. nov., a novel seaweed-degrading Bacteroidetes Hyun, D.W., Kim, J.Y., Kim, M.S., Shin, N.R., Kim, H.S., Lee, J.Y., Bae, J.W., 2015. bacterium with diverse putative polysaccharide utilization loci. Appl. Environ. Actibacter haliotis sp. nov., isolated from the gut of an abalone, Haliotis discus hannai, Microbiol. 82, 2975–2987. and emended description of the genus Actibacter. Int. J. Syst. Evol. Microbiol. 65, Sunda, W., Kieber, D.J., Kiene, R.P., Huntsman, S., 2002. An antioxidant function for 49–55. DMSP and DMS in marine algae. Nature 418, 317. Kim, J.H., Kim, K.Y., Hahm, Y.T., Kim, B.S., Chun, J., Cha, C.J., 2008. Actibacter sediminis Suzuki, T., Nakamura, T., Fuse, H., 2012. Isolation of two novel marine ethylene-assim- gen. nov., sp. nov., a marine bacterium of the family Flavobacteriaceae isolated from ilating bacteria, Haliea species ETY-M and ETY-NAG, containing particulate methane tidal flat sediment. Int. J. Syst. Evol. Microbiol. 58, 139–143. monooxygenase-like genes. Microb. Environ. 27 (1), 54–60. Koo, B.I., Lee, Y.S., Seo, M., Choi, H.S., Seah, G.L., Nam, T., Nam, Y.S., 2017. Image Tapia, J.E., González, B., Goulitquer, S., Potin, P., Correa, J.A., 2016. Microbiota influ- cytometric analysis of algal spores for evaluation of antifouling activities of biocidal ences morphology and reproduction of the Brown alga ectocarpus sp. Front.

9 J. Li, et al. Journal of Environmental Management 250 (2019) 109459

Microbiol. 7, 197. Van Apeldoorn, M.E., Van Egmond, H.P., SPEIJERS, G.J., BAKKER, G.J., 2007. Toxins of Thiel, V., Brinkhoff, T., Dickschat, J.S., Wickel, S., Grunenberg, J., Wagner-D bler, I., cyanobacteria. Mol. Nutr. Food Res. 51, 7–60. Simon, M., Schulz, S., 2010. Identification and biosynthesis of tropone derivatives Wang, J.G., Li, W.Q., 2013. A demonstration area of island reef ecological restoration will and sulfur volatiles produced by bacteria of the marine Roseobacter clade. Org. be built in Changdao. Shandong Fish. 5 59-59. (in Chinese). Biomol. Chem. 8, 234–246. Wang, H., Smith, H.L., Kuang, Y., Elser, J.J., 2007. Dynamics of stoichiometric algae- Thomas, F., Barbeyron, T., Tonon, T., Génicot, S., Czjzek, M., Michel, G., 2012. bacteria interactions in the epilimnion. SIAM J. Appl. Math. 68, 503–522. Characterization of the first alginolytic operons in a marine bacterium: from their Xu, F.L., Duan, J.Z., Lin, C.G., Hou, B.R., 2015. Influence of marine aerobic biofilms on emergence in marine Flavobacteriia to their independent transfers to marine corrosion of 316L stainless steel. J. Iron Steel Res. 22, 715–720. Proteobacteria and human gut Bacteroides. Environ. Microbiol. 14, 2379–2394. Yu, S.X., Pang, Y.L., Wang, Y.C., LI, J.L., Qin, S., 2017. Spatial variation of microbial Vairappan, C.S., Chung, C.S., Hurtado, A., Soya, F.E., Lhonneur, G.B., Critchley, A., 2008. communities in sediments along the environmental gradients from Xiaoqing River to Distribution and symptoms of epiphyte infection in major carrageenophyte-produ- Laizhou Bay. Mar. Pollut. Bull. 120, 90–98. cing farms. J. Appl. Phycol. 20, 477–483.