Bacterial Community Composition of the Sea Grape Caulerpa Lentillifera: a Comparison

bioRxiv preprint doi: https://doi.org/10.1101/2021.06.30.450479; this version posted June 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

1 Bacterial community composition of the sea grape Caulerpa lentillifera: a comparison

2 between healthy and diseased states

3 Germán A. Kopprioa*, Nguyen Dinh Luyenb,c, Le Huu Cuongb,c, Anna Fricked, Andreas

4 Kunzmanne, Le Mai Huongb,c, Astrid Gärdesf,g

5 a Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany

6 b Institute of Natural Product Chemistry, Vietnam Academy of Science and Technology, Hanoi,

7 Vietnam

8 c Graduate University of Science and Technology, Vietnam Academy of Science and

9 Technology, Hanoi, Vietnam

10 d Leibniz Institute of Vegetable and Ornamental Crops, Großbeeren, Germany

11 e Leibniz Centre for Tropical Marine Research, Bremen, Germany

12 f University of Applied Sciences, Bremerhaven, Germany

13 g Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven,

14 Germany

15 * Corresponding author at: Chemical Analytics and Biogeochemistry, Leibniz Institute of

16 Freshwater Ecology and Inland Fisheries, Müggelseedamm 301, 12587 Berlin, Germany. E-

17 mail: [email protected]

18 Key words: Vietnam, seaweed, aquaculture, green caviar, 16S rRNA diversity

20 Summary

21 The bacterial communities of the sea grape Caulerpa lentillifera were studied during a disease

22 outbreak in Vietnam. The Rhodobacteraceae and Rhodovulum dominated the composition of

23 healthy C. lentillifera. Clear differences between healthy and diseased cases were observed at

24 order, genus and Operational Taxonomic Unit (OTU) level. Bacterial diversity was lower in

25 healthy C. lentillifera, probably because of antimicrobial compounds from the macroalgae and/or

26 from Clostridium, Cutibacterium or Micrococcus bacteria. The likely beneficial role of

27 Bradyrhizobium, Paracoccus and Brevundimonas strains on nutrient cycling and phytohormone

28 production was discussed. The white coloration of diseased C. lentillifera may not only be

29 associated with pathogens but also with an oxidative response. Aquibacter, Winogradskyella

30 and other OTUs of the family Flavobacteriaceae were hypothesized as detrimental bacteria, this

31 family comprises some well-known seaweed pathogens. Moreover, Thalassobius OTU 2935

32 and 1635 may represent detrimental Rhodobacteraceae. Phycisphaera together with other

33 Planctomycetes and Woeseia were probably saprophytes of C. lentillifera. This study offers

34 pioneering insights on the co-occurrence of C. lentillifera-attached bacteria, potential detrimental

35 or beneficial microbes, and a baseline for understanding the C. lentillifera holobiont. Further

36 metagenomic and biotechnological approaches are needed to confirm functions of some

37 microbes on this macroalgae to enhance food security in the tropics.

38 Introduction

39 The sea grape or green caviar Caulerpa lentillifera is a green macroalgae widely cultivated in

40 tropical countries of the Indo-Pacific region, and its market as seafood delicacy has been

41 expanded drastically in the last decades. Not only C. lentillifera flavor, vesicular ramuli and

42 succulent texture which resembles caviar, but also elevated contents of polyunsaturated fatty

43 acids, antioxidants, vitamins and trace elements (Saito et al., 2010; Paul et al., 2014; de

44 Gaillande et al., 2017; Yap et al., 2019), together with its marketing as functional food increased

45 exponentially its demand. Moreover, the combination of the high nutritional quality of C.

46 lentillifera with its simple and low-cost cultivation transforms this macroalgae in a promising

47 candidate to enhance food security of tropical countries (de Gaillande et al., 2017; Stuthmann et

48 al., 2021). However, one of the major factor contributing to the worldwide decline of macroalgal

49 populations are microbial diseases (Egan et al., 2014) and C. lentillifera aquaculture is currently

50 endangered by outbreaks.

51 Macroalgae provide a nutrient-rich niche for microbes and some bacteria are capable to invade

52 algal tissue degrading complex polymers causing disease. Agarases, carrageenases, alginases,

53 fucoidanases, fucanases, mannanases, cellulases and pectinases are depolymerizing enzymes

54 detected in several marine bacteria for the breakdown of algal cell walls (Goecke et al., 2010).

55 Moreover, the low genetic diversity of cultured algae and their tight distribution in aquaculture

56 settings facilitate the rapid spread of detrimental microbes. Several bacterial diseases have

57 been reported in commercial macroalgae such as the rote spot and hole-rotten diseases caused

58 by Pseudomonas spp. in Saccharina japonica, rotten thallus syndrome by Vibrio sp. in

59 Gracilaria verrucosa, or Anaaki by Flavobacterium spp. in Pyropia yezoensis (Goecke et al.,

60 2010b; Egan et al., 2014; Ward et al., 2020). Nevertheless, the role of microbes is not only

61 detrimental but can also be beneficial.

62 Some bacteria are essential for algal health, growth and development. Beneficial bacteria

63 attached to macroalgae induce morphogenesis, fix nitrogen, produce phytohormones, release

64 antifouling and antimicrobial compounds, transport metabolites and nutrients, detoxify

65 pollutants, contribute to algal reproduction and are key for their adaptation to new environments

66 (Aires et al., 2013; Hollants et al., 2013; Singh and Reddy, 2014). The relation between

67 macroalgae and bacteria is generally mutualistic, and bacteria are mainly benefited with organic

68 substrates for their metabolism and a stable micro-environment protected from predators and

69 changing environmental conditions. The relations between macroalgae and bacterial

70 communities are so tight and reciprocal that the whole entity is considered a holobiont (Egan et

71 al., 2013; Arnaud-Haond et al., 2017; Califano et al., 2020). Furthermore, the bioactive

72 compounds produced by microbes in the holobiont have an enormous potential for drug

73 discovery and biotechnological applications (Friedrich, 2012; Luyen et al., 2019).

74 Despite the commercial importance of C. lentillifera and its relevance for human nutrition under

75 future climate-driven and overpopulation scenarios, studies about their microbiome are very

76 limited. Liang et al., (2019) described a disease in C. lentillifera in Chinese aquaculture systems

77 characterized by a dark-green biofouling, pink-colorated and missing ramuli. In this particular

78 case, Bacteroidetes and Cyanobacteria dominated the bacterial communities of diseased C.

79 lentillifera. Although recent advances in the study of the macroalgal microbiome using next

80 generation techniques, the information is still limited and mostly derived from culture methods

81 with their intrinsic limitations. The 16S rRNA gene approach offers broader insights on the

82 natural composition of bacterial communities attached to algae and plays an important role in

83 understanding algal diseases (Egan et al., 2014; Kopprio et al., 2021). Aims of this work were:

84 1) to characterize the bacterial communities of C. lentillifera in Vietnamese aquaculture, and 2)

85 to assess the effect of an unknown disease on its bacterial community composition. We

86 hypothesize strong differences in bacterial communities of C. lentillifera between healthy and

87 diseased cases.

88 Results

89 The order Rhodobacterales (class Alphaproteobacteria) and the genus Rhodovulum of the

90 mentioned order presented the highest relative sequence abundance in C. lentillifera at each

91 respective taxonomic level (Fig. 1). The Rhodobacteraceae was the only family detected within

92 the order Rhodobacterales. According to the Mann-Whitney test, the mean relative abundance

93 of Clostridiales (phylum Firmicutes) was significantly higher in healthy C. lentillifera, whereas the

94 abundances of Flavobacteriales (phylum Bacteroidetes), Phycisphaerales (phylum

95 Planctomycetes) and Steroidobacterales (class Gammaproteobacteria) characterized diseased

96 C. lentillifera thalli. The 99.7 % of the OTUs for the order Flavobacteriales corresponded to the

97 family Flavobacteriaceae. The trend observed at order level was similar at genus level: the

98 relative sequence abundance of Clostridium sensu stricto 7 (Clostridiales) was significantly

99 higher in healthy cases, while Aquibacter and Flavobacteriaceae unclassified (Flavobacteriales),

100 Phycisphaera (Phycisphaerales) and Woeseia (Steroidobacterales) were typical of diseased

101 cases. Without significant differences, other abundant genera were Rhodovulum, Cutibacterium

102 and Paracocccus for healthy C. lentillifera, while Thalassobius, Tropicibacter and Blastopirellula

103 for diseased C. lentillifera.

104

105 Fig 1 Mean relative sequence abundance (± standard deviation) of the main orders and genera in healthy and

106 diseased individuals of the sea grape Caulerpa lentillifera. (*) indicates significant differences at p < 0.05 according to

107 Mann-Whitney test. Caption superscript: shows correspondence between order and genus (e.g., Rho =

108 Rhodobacterales). uncl.: unclassified, Aphaproteobact.: Alphaproteobacteria, Clostr.: Clostridium, Cand. Kaiserbact.:

109 Candidatus Kaiserbacteria, Flavobact.: Flavobacteriaceae, mar. gr.: marine group, Methyloligel.: Methyloligellaceae

110 PERMANOVA revealed significant differences between the healthy and diseased cases at order

111 level (Pseudo-F = 3.89, p = 0.016). According to SIMPER analyses, the total dissimilarity

112 between healthy and diseased cases was 41.3%. The orders which presented significant

113 differences in the Mann-Whitney test were also important contributors to the dissimilarities and

114 evidenced the same trend in healthy or diseased C. lentillifera (Table I). Other relevant orders

115 with higher percentages of dissimilarities but without significant differences were

116 Propionibacteriales and Betaproteobacteriales for the healthy cases, while Saccharimonadales

117 and Verrucomicrobiales for the diseased cases. Furthermore, PERMANOVA detected

118 significant differences at OTU level between healthy and diseased C. lentillifera (Pseudo-F =

119 3.12, p = 0.015). According to SIMPER analysis, the total dissimilarity at OTU level was 71.3%

120 and the main OTUs contributing to this value are detailed in Table I.

121 Table I Main orders and operational taxonomic units (OTUs) of the sea grape Caulerpa lentillifera contributing to the

122 dissimilarity (41 and 71 % in total, respectively) according to SIMPER analyses. Taxa are grouped based on their

123 dominance in healthy or diseased cases.

124

125 The OTUs of order Clostridiales, typical of healthy C. lentillifera, were Clostridium sensu stricto

126 7 4975 and 1787 (Table I). Other OTUs dominating with elevated percentages of dissimilarity in

127 the healthy cases were those of the genera: Paracoccus, Spongiimonas, Cutibacterium,

128 Aliihoeflea, Pelomonas, Brevundimonas and Bradyrhizobium. In the case of diseased cases, the

129 major OTUs were those of Flavobacteriaceae unidentified, Aquibacter, Winogradskyella,

130 Aureicoccus and Ulvibacter for the order Flavobacteriales (all belonging to the family

131 Flavobacteriaceae), Phycisphaera for the order Phycisphaerales and Woeseia for the order

132 Steroidobacterales. Other OTUs with elevated percentages of dissimilarity in the diseased

133 cases were Methyloligellaceae unclassified 0867, Thalassobius 2935, Pir4 lineage 0189 and

134 JGI 069-P22 unclassified 0837. A list with other relevant OTUs according to their dissimilarity is

135 presented in table I. Moreover, the NMDS ordination of C. lentillifera samples at OTU level (Fig

136 2) suggested contrasting bacterial communities between healthy and diseased cases .

137

138 Fig 2 Non-metric Multi-Dimensional Scaling (NMDS) ordination of healthy and diseased individuals of the sea grape

139 Caulerpa lentillifera at Operational Taxonomic Unit (OTU) level

140

141 Fig 3. Heatmap of the main Operational Taxonomic Units (OTUs) on healthy (H) and diseased (D) individuals of the

142 sea grape Caulerpa lentillifera. (*) unclassified (**) sensu stricto 7

143 The heat map (Fig. 3) showed a similar cluster of 4 diseased C. lentillifera, while a variable

144 ordination of the other cases. OTUs associated exclusively to diseased status were Aquibacter

145 3662, Flavobacteriaceae unclassified 2304, Woeseia 0634, Phycisphaera 3117 and Muricauda

146 2354; while those exclusively detected in the healthy status were Bradyrhizobium 1899,

147 Paracoccus 4667 and Paracoccus 2980. OTUs of the genera JGI 069-P22 unclassified,

148 Thalassobius, Saccharimonadales unclassified, Flavobacteriaceae unclassified,

149 Winogradskyella, Aureicoccus, Pir4 lineage, Tropicibacter, Algisphaera, Cellvibrionaceae

150 unclassified and Aquibacter dominated mainly in the diseased cases. Other OTUs which

151 dominated but not exclusively in the healthy cases are displayed in the heat map. The inverse

152 Simpson indexes at the bottom of the heat map indicated mainly a higher diversity in diseased

153 C. lentillifera.

154 Discussion

155 Main composition and potential beneficial bacteria

156 The bacterial communities of C. lentillifera presented a similar composition than other green

157 algae at higher taxonomic levels. The dominance of Alphaproteobacteria and Bacteroidetes has

158 been reported in green macroalgae and some Caulerpa species (Friedrich, 2012; Aires et al.,

159 2013; Singh and Reddy, 2014). The order Rhodobacterales and family Rhodobacteraceae

160 dominated the bacterial communities of C. lentillifera in this particular case from the Vietnamese

161 aquaculture. Bacteria within the order Rhodobacterales are generally surface colonizers and

162 facilitate the settlement of microbial communities with the production of extracellular polymeric

163 substances (Kopprio et al., 2020). According to Simon et al. (2017), marine Rhodobacteraceae

164 are characterized by genes for the degradation of sulfated polysaccharides from algae,

165 production of phytohormones, metabolism of osmolytes, transport of metals and detoxification.

166 The bacterial communities at lower taxonomic levels are generally highly variable in seaweeds

167 and their composition may be associated with a particular function within the holobiont. The

168 microbiome composition depends generally on the geographic location, environmental factors,

169 seaweed tissues, developmental stage and even among local individuals (reviewed by

170 Friedrich, 2012). Burke et al., (2011) explain the pattern of bacterial colonization on a green

171 macroalgae with the competitive lottery model, according to this model different species with

172 similar functional traits can occupy the same niche depending on a stochastic probability. The

173 highest relative abundance of Rhodobacterales coincided with the results obtained in C.

174 lentillifera from China (Liang et al., 2019); nevertheless, one of the differences was in the

175 dominant genus within this order: Leisingera in contrast to Rhodovulum in our study. Moreover,

176 the last authors reported a higher abundance Planctomycetales and Oceanospirillales in healthy

177 C. lentillifera and not the elevated values of Clostridiales observed in this study.

178 Rhodovulum and particularly Paracoccus are Rhodobacteraceae with potential beneficial roles

179 for C. lentillifera. Rhodovulum species have a high metabolic versatility with the capability to

180 degrade organic pollutants, to produce polymers and to contribute with photosynthetic functions

181 (Khandavalli et al., 2018; Foong et al., 2019; Baker et al., 2021). Paracoccus is a common

182 genus among seaweed-associated bacteria with a key role in the cycle of nitrogen and in the

183 production of siderophores (Mei et al., 2019). Paracoccus strains promote the growth and the

184 morphogenesis in Ulva species (Ghaderiardakani et al., 2017) and were described as auxin

185 producers (Kurepin et al., 2014). Plant hormone production seems to be widespread in various

186 genera of marine bacteria (Goecke et al., 2010). Furthermore, Paracoccus sp. presented

187 algicidal activity (Zhang et al., 2018) and some members of this genus might contribute with

188 antifouling activities. The macroalgal surfaces constitute a highly competitive niche for nutrient

189 and space.

190 The likely production of antimicrobial compound of C. lentillifera may explain partially the low

191 diversity in healthy C. lentillifera. The same diversity trend was reported comparing healthy and

192 diseased C. lentillifera from the Chinese aquaculture (Liang et al., 2019). Some Caulerpa

193 species contain antibacterial compounds such as alkaloids, terpenoids, phenols and flavonoids

194 (Goecke et al., 2010; Yap et al., 2019; Zainuddin et al., 2019). Moreover, strains of Clostridium

195 sensu stricto 7 and Cutibacterium may reduce diversity with the production of antimicrobial

196 metabolites in healthy C. lentillifera. Some green algae provide a habitat for Clostridium species

197 and even for potential pathogens (Chun et al., 2013). Clostridium spp. can catabolize several

198 algal polymers (Song et al., 2011), have a likely function of copper detoxification in Codium

199 tormentosum (Le Pennec and Gall, 2019), and are sources of novel antimicrobial compounds

200 (Schieferdecker et al., 2019; Pahalagedara et al., 2020). A new thiopeptide antibiotic as

201 microflora modulator was detected on Cutibacterium sp. (Claesen et al., 2020) and some

202 species of this genus might produce antibiotics on Kappaphycus striatus (Kopprio et al., 2021).

203 A similar role on algal defense is suspected in the other Actinobacteria Micrococcus spp. (e.g.,

204 Hollants et al., 2013). In addition, this genus together with Bradyrhizobium were reported as

205 beneficial endophytic bacteria in many terrestrial plants with agronomic value (Afzal et al.,

206 2019).

207 Bradyrhizobium and Allihoeflea of the order Rhizobiales may participate in the cycle of nitrogen

208 and the production of phytohormones. “Rhizobacteria” were extensively studied in terrestrial

209 plants because of their ability to fix nitrogen and to modify genetically their host. Some

210 organisms of the family Rhizobiaceae presented growth-enhancing and probiotic properties on

211 green microalgae (Rivas et al., 2010). Furthermore, an endosymbiotic bacterium of this taxa

212 was responsible for the nitrogen supply in Caulerpa taxifolia (Chisholm et al., 1996).

213 Bradyrhizobium japonicum increases the biomass and starch content of the green microalgae

214 Chlamydomonas reinhardtii (Xu et al., 2016) and some strains of B. japonicum are producers of

215 the several phytohormones such as indole-3-acetic acid, gibberellic acid, zeatin, abscisic acid

216 and ethylene (Boiero et al., 2007).

217 A key role for C. lentillifera growth and health is supposed on strains of Brevundimonas spp.

218 Member of this genus establish a symbiotic relationship with green microalgae promoting their

219 growth, producing indole-3-acetic acid and enhancing nutrient uptake (Tate et al., 2013; Sforza

220 et al., 2018; Zhang et al., 2021). Some of their strains have a potential antifouling activity

221 against cyanobacteria (Lin et al., 2014) and in some terrestrial plants: alleviate toxicity, fix

222 nitrogen and promote growth (Singh et al., 2016; Naqqash et al., 2020). Pelomonas OTU 1964

223 sustains presumably a healthy status on C. lentillifera. This genus is common in the rhizosphere

224 of some plants with a nitrogen fixation function (Terakado-Tonooka et al., 2008) and some of

225 their aquatic strains produce the antibacterial compounds such as pelopuradazole (He et al.,

226 2014). Surprisingly, potential human pathogens like Escherichia-Shigella and Staphylococcus

227 were related to the healthy state of C. lentillifera according to SIMPER analysis. Hollants et al.,

228 (2013) reported these bacteria with the beneficial functions of defense and morphogenesis in

229 seaweeds, respectively.

230 Potential detrimental bacteria

231 The lack of production of antibacterial compounds by diseased C. lentillifera or the absence of

232 of some defense microorganisms may increase bacterial diversity. As mentioned in the above

233 section, this pattern was also observed in China, where the orders Flavobacteriales,

234 Phycisphaerales and Cellvibrionales dominated the diseased and decayed thalli of C. lentillifera

235 (Liang et al., 2019). With different disease symptoms, a similar pattern was observed in our

236 study: Flavobacteriales, Phycisphaerales and an unidentified genus of the family

237 Cellvibrionaceae were typical of diseased C. lentillifera. The bleaching and white coloration

238 symptom in C. lentillifera may not only be linked to a pathogen invasion, but also to an oxidative

239 burst response as a defense mechanism. Some Caulerpa species produce reactive oxygen

240 species like hydrogen peroxide against invasive organisms (Box et al., 2008).

241 The copiotrophic nature and ability to catabolize algal polymers of the Flavobacteriaceae gives

242 to this family, the potential to breakdown algal walls, to invade tissues and to cause disease

243 under certain conditions. Bacteroidetes and particularly Flavobacteriaceae are degraders of

244 complex biopolymers like sulfated polysaccharides from algal tissues (Yilmaz et al., 2016; Jain

245 et al., 2019). Many members of the Flavobacteriaceae have been confirmed or suspected as

246 causative agents of seaweed diseases (Goecke et al., 2010; Kumar et al., 2016; Ward et al.,

247 2020). In our particular case, we hypothesize as potential pathogens: strains of Aquibacter,

248 Winogradskyella, Aureicoccus, Ulvibacter and Muricauda. Aquibacter spp. characterized the

249 senescent state and decayed phase of the diatom Skeletonema dohrnii (Liu et al., 2021). In the

250 case of Winogradskyella spp., higher abundances have been observed on Pyropia yezoensis

251 with yellow spot disease (Liu et al., 2020) and on Delisea pulchra with a bleaching disease

252 (Kumar et al., 2016). On the other hand, Flavobacteriales are a common order among green

253 algae (Hollants et al., 2013) and Spongiimonas was linked to healthy C. lentillifera.

254 We hypothesize that Phycisphaera and Algisphaera spp. of the order Phycisphaerales were

255 opportunistic pathogens or saprophytes of C. lentillifera. As mentioned before, the order

256 Phycisphaerales was typical of the disease cases from the Chinese aquaculture and strains of

257 these genera were isolated from marine macroalgae presenting agarolitic activity (Fukunaga et

258 al., 2009; Yoon et al., 2014). Nevertheless, Planctomycetes are widespread in the epiphytic

259 microbial community of macroalgae, possess potential beneficial effects for their host like the

260 production of bioactive compounds, and are rarely identified as seaweed pathogens (Lage and

261 Bondoso, 2014). Some strains of Phycisphaera, Algisphaera, Pir 4 lineage and Blastopirellula

262 may be using their higher number of sulfatases for the degradation of algal polysaccharides

263 (Bondoso et al., 2017) from the dead or senescent tissue of C. lentillifera, which could be injured

264 by other pathogen or degraded because of an oxidative defense response. Other probable

265 saprophyte was Woeseia, species of this genus can utilize a broad range of energy-yielding

266 metabolisms and substrates (Mußmann et al., 2017). Some bacteria may be specialized on

267 small molecules derived from the breakdown of algal polymers and benefited from the

268 degradation of algal tissue. Members of the family Methyloligellaceae oxidize generally one

269 carbon atom molecules (Walker et al., 2021) and Patescibacteria (JGI 069-P22 and some

270 Saccharimonadales in this study) may be using monosaccharides because they have reduced

271 genes for polysaccharide catabolism in their simple genomes (Tian et al., 2020).

272 The classification of potential beneficial or detrimental bacteria at higher taxonomic levels in C.

273 lentillifera is not clear. The orders Verrucomicrobiales is well-known as active polysaccharide

274 degraders (Martinez-Garcia et al., 2012) but only a few genera were linked to algal disease. For

275 example, several OTUs of Rubritalea within this order were typical of Saccharina japonica with

276 symptoms of rotten hole disease (Zhang et al., 2020). Furthermore, the ability to metabolize

277 algal compounds of Rhodobacteraceae in a mutualistic relationship with seaweeds, may

278 became detrimental with some members of this family such as Thalassobius and Tropicibacter.

279 Thalassobius spp. characterized diseased Delisea pulchra (Kumar et al., 2016) and were

280 responsible of the direct lysis of a red-tide microalgae (Wang et al., 2010). Tropicibacter

281 multivorans has been detected in the microbiome of Caulerpa cylindraceae but little information

282 is available about its function (Rizzo et al., 2016). In this study case, Tropicibacter spp. may

283 contribute with the degradation of algal polymers.

284 Conclusions

285 Despite of different symptoms comparing cases from Vietnamese and Chinese C. lentillifera

286 cultures, a common bacterial pattern was observed on diseased organisms. A disease on C.

287 lentillifera may be caused by a community of detrimental bacteria together with changes on

288 algal response, and not only by a particular pathogen. Moreover, with this 16S rRNA approach

289 is not possible to identify clearly pathogens from saprophytes. A mutualistic relationship with a

290 particular bacteria may change and became detrimental under certain conditions; nevertheless,

291 clear differences between the healthy and diseased states were observed at several taxonomic

292 levels. This work explores changes in the bacterial community composition of C. lentillifera

293 under two conditions, detects co-occurrence but not causality, we cannot discard other

294 etiological agent not covered by the selected amplicon. Common patterns and roles were

295 inferred on this pioneer work from the Vietnamese aquaculture, which contribute to the

296 understanding of potential key players in the holobiont. A further metagenomic approach will

297 confirm the presence of functional genes for a particular microorganisms and their potential

298 biotechnological applications.

299 Experimental Procedures

300 Culture conditions, sampling and disease symptoms

301 Caulerpa lentillifera thalli were sampled in the culture facilities of the company VIJA at Van

302 Phong bay (N 12° 35' 17.67", E 109°13' 39.76") in the central eastern coastline of Vietnam. The

303 ponds for C. lentillifera culture were used previously for shrimp farming and contained

304 apparently a considerable load of organic matter. Water temperature in the ponds reached

305 ~31°C in May, with pH values of ~ 8.1, conductivity ~53 mS cm-1 and dissolved oxygen ~5.6 mg

306 L-1. The sea grape ponds were covered from direct sunlight radiance with shade cloths. Six

307 healthy and seven diseased thalli of C. lentillifera were collected during an outbreak of an

308 unknown disease. In contrast to the bright green color of healthy individuals (Fig. 1A), the

309 diseased C. lentillifera showed a marked tissue discoloration and a white biofilm on the external

310 circumference of the vesicular ramuli (Fig. 1B). After the described symptoms, the diseased

311 algae lost their turgid appearance and decayed with the consequent loss of their commercial

312 value.

313 314 Fig 4. A) Healthy thalli of Caulerpa lentillifera and aquaculture facilities in Vietnam. B) A comparison between healthy

315 (up) and diseased (down) individuals, the diseased individuals showed bleaching of thalli and a white biofilm on the

316 external circumference of the ramuli.

317 DNA extraction and amplification

318 Caulerpa lentillifera individuals were collected in sterile vials and preserved at -20°C until further

319 analysis. Under laboratory conditions, DNA was extracted basically according to Griffiths et al.,

320 (2000). Fragments of the thalli were immersed in 600 µL of hexadecyltrimethylammonium

321 bromide (CTAB) with 60 µL of 10 % SDS and 60 µL of 10 % N-lauroylsarcosin. Glass beads

322 were added and the tissue was homogenized in a FastPrep at 5 m s-1. Homogenates were

323 rinsed with 600 µL of phenol-chloroform-isoamylalcohol (25:24:1) and centrifuged at 16,000 g

324 and 4°C for 10 min. The upper aqueous layer was transferred to a clean reaction tube, mixed

325 with 2 volumes of 30 % polyethylene glycol (PEG) 6000 and 1.6 M NaCl and incubated at 4°C

326 for 120 min. Subsequently, the sample was centrifuged at 17,000 g and 4°C for 90 min, the

327 supernatant was carefully removed and the pellet was washed with ice-cold 70% ethanol. The

328 pellet was air-dry at 37°C for a few minutes, dissolved in PCR grade water and stored at -20°C.

329 The hypervariable region V3-V4 of the 16S rRNA gene was amplified with the set of primers

330 according to Klindworth et al., (2013): Bact-341F (5´-3´: CCT ACG GGN GGC WGC AG) and

331 Bact-785R (GAC TAC HVG GGT ATC TAA KCC)

332 Sequencing, bioinformatics and statistical analysis

333 The amplicon V3-V4 of the 16S rRNA gene was sequenced with a 2 x 300-bp paired-end run on

334 an Illumina MiSeq platform. Sequencing, removal of primer sequences and demultiplexing were

335 conducted by the company LGC genomics. Sequences were trimmed and merged using

336 Trimmomatic v0.36 (Bolger et al., 2014) and PEAR v0.9.8 (Zhang et al., 2014), respectively.

337 Operational Taxonomic Units (OTUs) were clustered by Minimum Entropy Decomposition MED

338 v2.1 (Eren et al., 2015) and their representatives were submitted to SilvaNGS (v132,

339 https://ngs.arb-silva.de/silvangs/) using a sequence similarity of one for clustering and the

340 remaining variables as default. Singleton, doubleton and sequences from mitochondria,

341 chloroplasts and archaea were removed from the analysis. A total of ~222,000 reads remained

342 after data curation and the mean OTU number per sample was ~17,100 ± 14,500 (± standard

343 deviation). Demultiplexed and primer-clipped sequences were deposited at the European

344 Nucleotide Archive (ENA) using the data brokerage service of the German Federation for

345 Biological Data (Diepenbroek et al., 2014) with the number PRJEB42826, in compliance with

346 the Minimal Information about any (x) Sequence (MIxS) standard (Yilmaz et al., 2011).

347 Pooling of taxa, removal of OTUs with poor alignment quality and relative sequence abundance

348 and diversity calculations were conducted in R v4.0.5 (R Core Team, 2021) and additional

349 packages. The relative sequence abundances of the main orders between the diseased and

350 healthy cases were compared with a Mann-Whitney test. Data were transformed, a Bray Curtis

351 similarity matrix was calculated, and differences between the states at order and OTU level

352 were evaluated using permutational multivariate analysis of variance (PERMANOVA). In case of

353 significance differences, similarity percentage analysis (SIMPER) was performed to detect the

354 main taxa contributing to dissimilarities. Samples at OTU level were ordinated by Non-metric

355 Multi-Dimensional Scaling (NMDS). A heat map based on the 60 most abundant OTUs,

356 covering the 64 ± 11 % of the total relative sequence abundance, was displayed to compare

357 healthy and diseased cases. Graphics and statistics were performed with R 4.0.5, Xact 7.21,

358 PRIMER v6 + PERMANOVA, and XLSTAT-Ecology

359 Acknowledgment

360 We are grateful with T. M. Duc for logistical support.

361 Data availability

362 16S sequencing data are available at ENA (https://www.ebi.ac.uk/ena/data/view/PRJEB42826).

363 References

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